Author: augmented_admin

Are you hitting a wall with Looker Studio’s limitations? You’re not alone!

A lot of teams start with this user-friendly tool – only to discover down the line that it can’t keep up with growing demands for complex data analysis and enterprise security.

Some of the most common complaints I’ve heard from Looker users include:

• The data modeling capabilities struggle to cope with complex analysis. 
• It doesn’t have enterprise-grade, row-level security. 
• Looker lacks advanced embed capabilities for client-side reporting.

And the good news is that there are several good alternatives out there that offer features to make up for these limitations!

In this post, I’ll walk you through 8 such Looker Studio alternatives that I’ve tried and tested over the years.

I’ve included a wide range of tools on my list: some are enterprise-grade, some are embed-friendly, and others are open-source data.

Use the comparison table below to quickly scan your options, or read on for an in-depth analysis of each platform to find the best tool for your specific requirements!

Looker Studio Alternatives: Table of Contents

• TL;DR: Top 3 Looker Studio Alternatives Compared
• 8 Looker Studio Alternatives (Tried and Tested)
• How to Choose the Best Looker Studio Alternative?
• Looker Studio Alternatives: Final Thoughts
• Looker Studio Alternatives: FAQs

TL;DR: Top 3 Looker Studio Alternatives Compared

Here’s a quick breakdown of the 3 best Looker Studio alternatives by their use cases:

 

1. Microsoft Power BI

Use Case: The Best All-Rounder for Most Businesses

Ideal for organizations of all sizes, especially those using Microsoft 365. It strikes the best balance between cost, user-friendliness, and powerful analytics, making it the most practical choice for the majority of teams.

 

2. Tableau

Use Case: The Gold Standard for Advanced Data Visualization.

The top choice for data professionals and enterprises that prioritize deep, exploratory data analysis and creating highly sophisticated, interactive dashboards. Best when visualization power is more critical than budget constraints.

 

3. Metabase

Use Case: The Top Choice for Open-Source & Embedded Analytics.

Perfect for startups, SMBs, and product teams needing a cost-effective, user-friendly tool for internal or embedded analytics. Its open-source core and intuitive interface lower the barrier to entry for self-service BI.

Quick Comparison: Top 3 Looker Studio Alternatives

Key Takeaways:

• Choose Power BI for the best balance of price, features, and ease of use.
• Go for Tableau for unmatched visualization capabilities and enterprise scale.
• Select Metabase for open-source flexibility and quick setup.

8 Looker Studio Alternatives (Tried and Tested)

As promised, here’s my list of the 8 best Looker Studio alternatives – I’ve selected them based on their data modeling capabilities, ease-of-use, embed features, and pricing.

Here’s how the list stacks up:

1. Tableau: The Gold Standard for Visual Analytics

2. Microsoft Power BI: The Best All-Rounder

3. Domo: The Unified Cloud Platform

4. Qlik Sense: The Leader in Associative Analytics

5. Sisense: Best for Embedded Analytics

6. Metabase: The Top Open Source Choice

7. Zoho Analytics: The Best for SMBs

8. Apache Superset: The Scalable Open Source Powerhouse

1. Tableau: The Gold Standard for Visual Analytics

Tableau is one of the most popular Business Intelligence and data visualization tools on the market.

It’s a strong Looker Studio alternative for anyone who wants to perform complex analysis on large datasets.

It also helps you create interactive, intuitive visualizations and dashboards.

Best For: Large enterprises and data professionals who require deep, exploratory data analysis, robust security, and scalable deployment options.

Key Features of Tableau

• Advanced Visualization Capabilities: You get access to an extensive library of charts, such as bar, Gantt and motion charts. Plus, the drag-and-drop interface is perfect if you want a tool that is easy to use for non-technical users.

• Powerful Data Connectivity: One of Tableau’s strengths is that it integrates very well with a range of data connectors – cloud databases, data warehouses, spreadsheets, and big data platforms. The Hyper data engine delivers quick querying and can analyze large datasets without lagging.

• AI-Powered Analytics (Tableau Pulse): This is my favorite Tableau feature. It provides AI-driven insights, natural language querying (through Ask Data), and automated explanations of data points (via Explain Data). 

If you like these features and want to explore them in detail, check out my guide on How to Use Tableau.

Potential Limitations of Tableau

• Tableau’s pricing might be too expensive for SMBs, startups, and solopreneurs.
• The learning curve is pretty steep compared to other Looker Studio alternatives.
• Its data cleaning capabilities are not the strongest. 

Tableau Pricing Information

Tableau uses a tiered, per-user subscription model billed annually. Simply put, you need at least one Creator license to use Tableau effectively.

 

• Creator: $115 per user/month, includes Tableau Desktop, Prep Builder, and a Cloud/Server license.
• Explorer: $70 per user/month for self-serve analysis on published data sources.
• Viewer: $35 per user/month for viewing and interacting with dashboards.

2. Microsoft Power BI: Best All-Round Looker Alternative

Next on my list is Microsoft Power BI – a unified, scalable business analytics platform designed to turn data into actionable insights.

Technically, it is a core component of the Microsoft Fabric ecosystem that offers integrated tools for both self-service and enterprise BI requirements.

Best For: Organizations already using Microsoft tools like Office 365 and Azure, seeking a cost-effective and user-friendly BI solution.

Key Features of Microsoft Power BI

• Seamless Microsoft Ecosystem Integration: Power BI comes with a native integration for Microsoft 365 apps – Teams, Excel, SharePoint, and Azure services. This means Microsoft users won’t need to switch platforms to get insights into their data.

• AI Copilot for Analytics: Power BI also features a robust integration with Microsoft’s Copilot AI. You can use it to generate reports, DAX calculations, and simple answers to data-based questions using text-based queries.

• Comprehensive Platform Components: Power BI consists of Power BI Desktop (a free app for in-depth data modeling + report creation), the core BI service (a cloud-based SaaS for publishing and sharing), and mobile apps.

Check out my blog on How to Use Power BI to explore the tool and see if the features meet your requirements.

Potential Limitations of Power BI

• Power BI can slow down when processing large/complex datasets.
• You’ll have to spend some time learning how to use the more advanced functions.
• Limited data prep capabilities – so you might have to use an ELT/ETL tool for prep.

Check out my blog comparing Power BI vs. Looker to find out which one is better for you.

Power BI Pricing Information

Apart from a Free plan for basic functionalities, Power BI offers three different pricing plans:

• Power BI Pro: $14 per user/month (paid yearly). Required for publishing, sharing reports, and collaborating with other Pro users.
• Power BI Premium Per User (PPU): $24 per user/month (paid yearly). Includes all Pro features, plus larger model sizes, and more frequent data refreshes (48/day vs. 8/day on Pro).
• Power BI Embedded or Microsoft Fabric: Variable, capacity-based pricing for embedding analytics into applications and enterprise-wide deployment.

3. Domo: A Unified Cloud Platform

Domo is a cloud-native business intelligence platform.

Its core strength is that it’s an all-in-one data analysis and visualization solution that also offers strong embed capabilities.

That is, Domo unifies data integration, transformation, visualization, and collaboration into a single, integrated environment.

Best For: Large enterprises + mid-sized orgs that need to consolidate data from numerous sources and agencies require robust embedded analytics capabilities.

Key Features of Domo

• Extensive Data Connectivity: One of my favorite things about Domo is that it provides over 1,000 pre-built connectors to cloud applications, databases, and proprietary systems. You can also integrate it with tools like Magic ETL for drag-and-drop data transformation.

• Robust BI and Analytics Suite: Domo’s interface is both intuitive and low-code – perfect for building interactive dashboards. You can also choose from over 150 chart types. Plus, you get tools for storytelling, alerts, and scheduled reporting.

• Domo.AI: Domo has also done a solid job of integrating AI throughout its platform. For example, you can create custom AI agents, generate SQL code with text prompts, and even build + deploy advanced models with Jupyter Workspaces integration.

Potential Limitations of Domo

• Domo is an enterprise-grade tool with expensive and complex pricing.
• Creating tailored visualizations with advanced features might be challenging for non-technical users.

Domo Pricing Information

Domo does not publish transparent pricing – it’s best to contact their sales for a custom quote.

However, from the clients I’ve worked with and my personal experience, I do know that the pricing model is primarily credit-based, with costs scaling based on data volume and usage.

For mid-sized companies, I’ve seen annual costs fall in the range of $20,000 and $50,000, while enterprise deployments can range from $50,000 to over $100,000.

4. Qlik Sense: Best for Associative Analytics

Next up, we have Qlik Sense – a powerful data analytics platform whose strength is free data exploration and discovery through its unique associative engine.

It’s a unique tool on my list that goes beyond traditional query-based tools by indexing all relationships within your data and allowing you to intuitively uncover hidden insights that might otherwise be missed!

Best For: Data analysts and enterprises that need to perform deep or exploratory data discovery across complex & diverse datasets.

Key Features of Qlik Sense

• Associative Analytics Engine: This is the core technology that differentiates Qlik Sense from other data visualization tools. It indexes every possible relationship in your data! So, when you make a selection, it instantly highlights related (white), selected (green), and unrelated (grey) data, revealing hidden patterns that help you quickly understand potential relationships within your data.

• AI-Powered Insights: Qlik uses AI to automatically generate and prioritize visual insights. It also tells you which charts will best represent your data, thus accelerating analysis and visualization. I also like that its AI-assisted data prep features help users combine and transform data from multiple sources.

• Flexible Deployment Options: You can opt for a fully-managed cloud SaaS solution (Qlik Sense Business), an enterprise-grade platform for multi-cloud or on-premises deployment (Qlik Sense Enterprise), or a free desktop version for individual use.

Potential Limitations of Qlik Sense

• The associative model might require some to get used to.
• You might need to configure data between Direct Query mode and in-memory leading for complex datasets. 

Qlik Sense Pricing Information

Qlik offers three different pricing plans:

• Desktop: A free version for individual use and learning.
• Business: Starts at $30 per user/month (billed annually).
• Enterprise: Custom pricing based on organizational requirements. 

5. Sisense: Built for Embedded Analytics

If you’re an agency, an enterprise or just a user that wants deep embed capabilities, Sisense is the best Looker Studio alternative on the market.

It’s a powerful BI platform that you can use to integrate customizable AI-powered analytics directly into other apps or software products.

While anyone who needs embed capabilities can use it, Sisense is designed primarily for organizations that need to provide data insights within their own ecosystems, whether for internal tools or customer-facing SaaS products.

Best For: Software companies and enterprises requiring deeply integrated, white-label embedded analytics within their applications.

Key Features of Sisense

• Fusion Embed + Compose SDK: You can engineer tailored data products and dashboards that closely match your app’s look and feel using popular web frameworks like React, Angular, and Vue.

• AI-Powered Insights: Sisense’s AI capabilities help you automate data analysis, generate predictive insights, and offer responses to text-based prompts. This makes Sisense very user-friendly – you don’t need deep technical expertise to uncover hidden trends or make data-driven decisions.

• Connectivity and Elasticube Engine: You can easily integrate data from sources like cloud data warehouses or on-premises databases. Plus, its proprietary ElastiCube engine can handle and analyze large, complex datasets efficiently – making it a strong option for lag-free performance in embedded scenarios.

Potential Limitations of Sisense

• Expensive, even when compared to some other enterprise-grade alternatives.
• You might need some time to familiarize yourself with the SDK capabilities to create custom embeds. 

Sisense Pricing Information

Sisense uses a custom-quote model – it doesn’t even have a public pricing page.

However, based on the clients I’ve worked with in the past, here’s the ballpark figure you can expect to pay:

• $10,000+ per year for self-hosted architecture.
• $21,000+ per year Sisense Cloud.

 

You might also have to pay more depending on the number of seats you need and the data volume (ElastiCube size) you want to service.

 

6. Metabase: The Top Open Source Choice

Metabase makes my list of the best Looker Studio alternatives as the best open-source business intelligence platform.

It makes data exploration and dashboard creation accessible to everyone, from non-technical business users and even professional data analysts.

What I like most about it is its user-friendly interface and quick setup, making it a popular choice for startups and small to mid-sized teams.

Best For: Startups, SMBs, and teams with limited budgets that need a quick-to-deploy, user-friendly BI tool for internal or embedded analytics.

Key Features of Metabase

• Intuitive No-Code Query Builder: Metabase’s visual query builder is what allows you to ask questions of their data through a point-and-click interface. That means you don’t need to write even a single line of code to explore data or create interactive reports.

• Flexible Deployment and Embedding: Metabase’s second core strength is that it offers an open-source version for self-hosting + paid cloud-hosted plans. And both versions feature solid embedding capabilities so you can easily integrate dashboards and charts into your own apps, with white-labeling options available on paid tiers.

• AI-Powered Assistance (Metabot): Metabase includes an AI assistant that helps you ask text-based queries, generate SQL code, and debug queries. So, you can accelerate data-powered workflows even if you don’t have a  dedicated data engineer on your team!
  

Potential Limitations of Metabase

• I’ve seen and heard a lot of users complaining that Metabase slows down when handling complex datasets.
• Metabase offers limited options (graphs, charts, etc) for data visualization.
• It’s not suited to direct advanced data modeling tasks.

Metabase Pricing Information

Metabase’s open-source version is free forever as long as you self-host it. Apart from this, it offers three different pricing options, each for a different functionality:

• Starter (Cloud): $85 per month (includes first 5 users, then $5/user/month).
• Pro (Cloud/Self-Hosted): $500 per month (includes first 10 users, then $10/user/month), also unlocks advanced embedding, white-labeling, and permissions.
• Enterprise: Custom pricing (starts at around $15,000 per year).

7. Zoho Analytics: The Best for SMBs

Zoho Analytics is my pick for SMBs, solopreneurs, and startups that need a powerful BI tool.

It is a self-serve BI and data analytics platform designed you can use to analyze data, create visualizations, and uncover insights quickly.

One thing I really like about Zoho is that it doesn’t compromise on the number of features it offers even though it doesn’t charge a lot.

For just $24/month, you get access to all of its features – a wide range of connectors, an AI-powered assistant, and pretty decent data analysis capabilities.

Best For: SMBs and startups looking for an affordable, user-friendly BI tool with good integration capabilities. Also perfect for anyone already using other Zoho products.

Key Features of Zoho Analytics

• Extensive Data Connectivity: Native integration with over 500 data sources, including popular business apps (Zoho CRM, Salesforce, QuickBooks), cloud data warehouses, databases, and flat files.

• AI-Powered Analytics (Ask Zia): You can ask Zia, Zoho’s AI assistant, text-based questions and it will generate answers, reports, and even KPI widgets. Zia also provides automated insights (Zia Insights) + predictive analytics, and can guide you through data prep and report building processes through a simple conversation.

• Pre-Built Analytics Templates: This functionality is pretty similar to Looker Studio’s Templates – Zoho Analytics also gives you access to hundreds of domain-specific, pre-built reports plus dashboards for sales, marketing, finance, HR, and other functions.

Potential Limitations of Zoho

• The total cost can mount quickly due to Zoho’s row-based pricing tiers.
• Non-technical users might need some time to become familiar with the more advanced features. 

Zoho Pricing Information

Zoho Analytics uses a transparent, tiered subscription model billed monthly or annually (with a 20% discount for annual billing). Let me quickly walk you through its pricing plans:

• Free Plan: Available for up to 2 users and 10,000 rows.
• Standard: ~$24 per month (billed annually) for 2 users and 0.5 million rows.
• Premium: ~48 per month (billed annually) for 5 users and 1 million rows.
• Enterprise: Custom pricing for 50+ users and 50+ million rows.

8. Cognos by IBM: The Enterprise Reporting Powerhouse

Last on my list of the best Looker Studio alternatives is IBM’s Cognos Analytics.

It is a comprehensive, enterprise-grade business intelligence platform designed for large organizations.

So, if you need robust reporting, stringent governance, and scalable deployment options – Cognos is a strong choice.

Plus, it goes beyond visualization to offer a unified environment for complex data modeling and AI-assisted analysis.

I also really like its pixel-perfect report generation that makes it very easy to create meeting-ready reports and dashboards.

Best For: Large enterprises and organizations in regulated industries that need highly governed, scalable BI solutions with powerful, traditional reporting capabilities.

 

Key Features of Cognos

• Augmented Analytics: You can ask text-based questions about your data and get AI-generated answers and insights. Cognos also features automated pattern detection, predictive forecasting, and smart visualization suggestions to help uncover hidden trends.

• Enterprise-Grade Reporting + Dashboards: Cognos is particularly known  for its high-performance, “pixel-perfect” reporting capabilities that you can use to create multi-page financial statements to interactive dashboards. You can also format the layout of your reports to meet strict corporate or regulatory standards.

• Flexible Deployment and Scalability: Cognos can be deployed on-premises, as a service on IBM Cloud, or in a hybrid model. You can also deploy it as a part of any cloud (including AWS, Azure, and GCP) via Kubernetes.

Potential Limitations of Cognos by IBM

• One problem with Cognos is that you’ll need either a team of data engineers or a data visualization consultant to make the most of its complex features.
• Its visualization options are limited compared to Tableau or Power BI. 

Pricing Information

IBM Cognos Analytics uses a tiered subscription model – but you can expect to pay around $25/user/month for its starting plan.

 

How to Choose the Best Looker Studio Alternative?

To choose the best Looker Alternative, I recommend considering 4 main factors:

• Your Primary Use Case: First, you need to know what capabilities you absolutely need your BI tool to have. Is it self-service analytics for business users, embedded analytics for your product, or enterprise-wide reporting with strict governance? This will immediately narrow your options.

• Technical Resources Available to You: Next, assess the technical skills and knowledge of your team. For example, if you’ve got data engineers with good experience of handling BI tools, Metabase might help you cut down on your expenses. On the other hand, Sisense might be expensive, but perfect for enterprise-grade requirements.

• Your Data Sources: Make sure that the tool you’re choosing can natively connect to your critical data sources (e.g., CRM, databases, cloud warehouses). If not, you might want to evaluate whether it’s worth the effort to get a more affordable Looker Studio and also work with another ELT/ETL tool on top.

• Total Cost of Ownership (TCO): Lastly, don’t just look at the initial license fee. Consider costs for implementation, training, additional connectors, and scaling users.

 

My suggestion: make a list of the features/capabilities you need, and then compare different tools based on their user experience and pricing to find the best option.

And don’t forget to use free trials to explore the platform with your own data before committing!

Looker Studio Alternatives: Final Thoughts

Through this blog, I’ve walked you through the 8 best Looker Alternatives on the market.

I’ve also shared with you the factors you should consider to choose one that suits your data visualization and analysis needs.

And if you’re still not sure which Looker alternative best fits your requirements, reach out to us at Augmented Tech Labs!

Over the 10 years that we’ve been in the data visualization industry, we’ve worked extensively with all the Looker Studio alternatives we’ve mentioned above.

So, connect with us for a free consultation, and we’ll help you find the right data visualization tool that will align with your operational needs.

Looker Studio Alternatives: FAQs

1. What is the best all-around Looker Studio alternative?

Microsoft Power BI is the top all-round Looker Studio alternative – it offers powerful analytics, seamless Microsoft 365 integration, and a cost-effective freemium model suitable for most organizations.

2. When should I hire a data visualization consultant?

You should hire a data visualization consultant when you need expert guidance to select, implement, and customize a BI platform. Data visualization consultants (like us at Augmented Tech Labs) ensure the tool aligns with your specific data infrastructure, security needs, and business objectives for maximum ROI.

3. What are the best dashboard creation tools for enterprises?

For large enterprises, the best dashboard creation tools are Tableau for advanced analytics and Domo for unified data consolidation. Both offer robust security, scalability, and powerful, interactive visualization capabilities for complex data environments.

4. Are there any capable free data visualization tools?

Yes, capable free data visualization tools include Microsoft Power BI Desktop and the open-source version of Metabase. These platforms offer strong core features for individual users and small teams to build reports and dashboards.

5. Which open-source tool is best for embedded analytics?

For open source data visualization and embedding, Metabase is a solid choice. Its intuitive interface and flexible deployment options make it ideal for integrating analytics directly into your own applications and software products.

If you’re an enterprise, agency, or even a data analyst, you know that collecting data is easier than ever.

You’ve got CRMs, Cx platforms, Revenue Management Systems, ads analytics, and more.

But when it comes to analyzing this data to capture the key insights? It often becomes a huge challenge!

That’s where Looker Studio comes in!

It solves the critical problem of data silos by connecting to over 1,200 data sources like Google Analytics, Google Ads, and SQL databases, allowing you to create a “single source of truth”.

In this comprehensive guide, I will help you:

• Understand the fundamentals of Looker Studio and its core capabilities.
• Discover the key features and benefits of Looker Studio.
• Build your first interactive Looker Studio dashboard with a step-by-step tutorial.
• Get answers to frequently asked questions about implementing it effectively.

Let’s dive in!

What is Looker Studio: Table of Contents

• What is Looker Studio?
• Key Features of Looker Studio
• Benefits of Looker Studio: Why You Should Consider Using It
• How to Get Started with Looker Studio?
• Looker Studio Pricing Guide
• Augmented Tech Labs: Your Looker Data Visualization Specialist
• What is Looker Studio: FAQs

What is Looker Studio?

Looker Studio is Google’s free, web-based data visualization and business intelligence (BI) tool. Its main task is to transform raw data into clear, customizable, and interactive dashboards + reports.

And if you’ve ever spent hours trying to create a report by finding data from 1, 2, or 10 different spreadsheets and data exports – you already understand the problem Looker Studio was built to solve!

Image: Sample Looker Studio Report

From Google Data Studio to Looker Studio: A Brief History

Looker was not actually created by Google – it was a standalone business intelligence product under the company of the same name. However, Google did have its own Google Studio for data visualization.

That changed in 2022 when Google acquired the business intelligence company Looker and rebranded the product as Looker Studio.

With this move, Google integrated Looker deeply into its Cloud ecosystem, now known as the Looker family of products.

Why Use Looker Studio vs. Other BI Tools?

There are a lot of data visualization tools on the market: Tableau, Power BI, Domo, Qlik – the list is pretty big!

So, when and why should you choose Looker Studio?

Think of it this way: while tools like Tableau are powerful data engines for deep, complex analysis, Looker Studio is the premier tool for data communication.

That is, its core strength lies in its accessibility and ease of use!

Google has designed the new-look Looker Studio specifically for:

• Marketing Professionals to create client-facing reports.
• Business Analysts to quickly build dashboards for team leads.
• Agency Owners (like us at Augmented) to generate performance reports.

So, while it might not be the best option out there if you want to handle data running into billions of rows, its cost (free!), user-friendly interface, and speed of dashboard creation make it the preferred tool for most business reporting needs!

To find out how Looker compares with other tools, check out my blog on Power BI vs. Looker!

Key Features of Looker Studio

Now that we’ve discussed what Looker Studio is, let me walk you through its best feature: 

1. Extensive Data Connectivity

Looker Studio’s core strength is definitely its ability to connect to a vast array of data sources.

If you primarily rely on the Google ecosystem and use Analytics, Ads, Sheets, or BigQuery – Looker is the best data visualization tool for you. It offers deep native integration and can easily extract and visualize data from these platforms.

On top of this, it’s also highly compatible with SQL databases, social media platforms, and CRM systems.

This is why Looker Studio is considered one of the best tools for creating a “unified, single source of truth” for client-facing analysis.

Image: Looker Data Connectors

2. Drag-and-Drop Report Building

Handling a lot of data and data sources is already a complex task – so you might be looking for a tool that makes visualization easier, not harder!

If this sounds familiar, Looker Studio is ideal for you. It comes with an intuitive interface that requires no coding skills at all.

To build interactive reports and dashboards, all you have to do is simply drag and drop elements like charts, graphs, and tables onto a “canvas”.

This user-friendly design makes advanced data visualization accessible to users of all technical levels – whether you’re a marketer or an analyst.

3. Rich Visualization Library

When it comes to the actual visualization part, Looker Studio offers a wide variety of configurable charts and graphs.

You can choose from standard options like line, bar, and pie charts to more advanced visualizations such as geo maps, bubble graphs, and pivot tables.

This flexibility ensures you can present a type of visualization that suits both – the nature of your data and the expectations of your audience.

4. Real-Time Collaboration and Sharing

Like all other Google Workspace tools, Looker Studio is hard-wired for collaboration.

That means multiple users can view and edit reports simultaneously. Plus, all the changes are reflected immediately – i.e. in real time.

You can also share reports via link, schedule email deliveries, or embed dashboards directly into websites, Google Sites, or intranet pages.

5. Custom Branding and Theming

If you’re operating an agency and want to create customised reports that align with your brand’s identity, Looker Studio is your most affordable and accessible option.

That’s because it gives you full control over the appearance of your reports – you can fully customize layouts, apply color themes, and add branding elements (logos + images).

So, if you want to create white-labeled, professional reports that align with your or your clients’ brand guidelines, Looker’s got you covered!

6. Interactive Dashboards with Filter Controls

My favorite Looker Studio feature is definitely its dashboard capabilities.

It helps you create dynamic reports by adding interactive elements that also update based on real-time information.

Plus, you can embed viewer filters and data range controls directly into your Looker Studio dashboards.

In short, you can empower your team, clients, or users to explore the data on their own terms – turning any report into a flexible template for personalized analysis!

Image: Sample Looker Dashboard

7. Calculated Fields and Custom Formulas

Does Looker support more sophisticated analysis?

It does! Looker Studio helps you create custom metrics and dimensions by using “calculated fields”.

And with the integration of Gemini in Looker Studio Pro, you can even generate these formulas using text prompts like “Merge city and state rows”.

This feature thus both enables and simplifies complex data manipulation for non-technical users.

8. Template Gallery for Rapid Creation

Once you log into Looker Studio, you can start building your first report by using any one of the many pre-built report templates.

These templates cover various use cases (like marketing, sales, and advertising) and can be customized with your data sources.

Benefits of Looker Studio: Why You Should Consider Using It

Looker Studio isn’t just a good tool in itself – it’s also a pretty great alternative compared to other BI tools for a lot of reasons:

• Significant Cost Reduction: You can start your data visualization journey for free with Looker Studio. So, whether you’re an enterprise, startup, or analyst, you can eliminate the (sometimes highly) expensive licensing fees associated with many other enterprise-level Business Intelligence (BI) tools (like Domo).

 

• Efficient Data Aggregation: Since Looker Studio features deep integration with multiple sources, you never have to worry about performing manual, repetitive tasks like exporting CSVs and combining them in spreadsheets.

 

• Quick Collaboration: Looker Studio creates a “single source of truth,” which ensures that everyone in your organization has access to the same live data. So, your employees will never make conflicting decisions because of “bad data”.

 

• Data-Driven Decision Making: This is the most important Looker Studio benefit – its interactive dashboards help you explore data independently. They move from static snapshots to dynamic analysis so that you can make faster, more confident decisions.

 

• Scalable Client Reporting: If you’re operating an agency, Looker Studio’s ability to fully white-label reports is definitely a huge plus. It basically enables you to deliver a seamless, professional reporting experience to your clients.

 

• Ease of Use for Non-Technical Users: The intuitive, drag-and-drop interface is ideal if your team has non-technical personnel who also need to build reports and find answers without relying on specialists.

 

• Deeper Google Ecosystem Integration: For teams that are already using Google products, Looker Studio offers native integration with Analytics 4, Google Ads, and Sheets. As a result, you can expect a smooth and stable report-building and data visualization experience!

Personally, I’ve had great success in creating data visualization with Looker Studio for a wide range of clients – technical + non-technical users, agencies that use Google or other ecosystems, and even enterprises or startups!

How to Use Looker Studio: Step-by-Step Guide to Building Your First Dashboard

Next, let’s get to the slightly more challenging part – how to use Looker Studio to create a reporting dashboard.

While it may seem challenging, don’t worry – I’ll walk you through the step-by-step process that will make it extremely easy for you to get started.

Let’s break it down:

Step 1: Access Looker Studio and Create Your First Report

• Go to the Looker website – lookerstudio.google.com. 
• Sign in with your Google account. 
• Click the button that says “+ Create” and select “Report” from the dropdown menu.

Image: “Create A New ‘Report’” Window in Looker Studio

You’ll see a pop-up window that’ll ask you to “Add Data to Report”.

Step 2: Connect Your Data Source

To “Add Data to Report,” you have two options: Connect to Data or My Data Source. 

But since you’ve just started with Looker Studio, you should first “Connect to Data” – i.e. select a data source.

Image: “Add Data to Report” Window, Looker Studio

In this window, Looker Studio will present you with a list of hundreds of connectors.

You can either scroll through the options or use the search bar to find your data source (e.g., “Google Analytics 4”).

• For Google Analytics 4: You’ll be asked to select the correct Account, Property, and View.
• For Google Sheets: You’ll need to select the specific spreadsheet and worksheet.

Once you authorize the connection, just click “Add to Report.”

You will now see a blank canvas (i.e. your report) and the data fields available from your source on the right-hand side.

Step 3: Build Your Dashboard with Visualizations

This is where the magic happens – you can use the toolbar at the top to add charts.

I suggest starting with a few key visualizations:

1. Scorecard: Click the “Add a Chart” icon and select the scorecard (the number “123” icon). This displays a single, important metric (like Users or Total Revenue). In the “Data” tab on the right, choose your metric from the available fields.
   
   
2. Time Series Graph: Add a new chart and select the time series graph. This is perfect for showing how a metric (like “Sessions”) changes over time. Set the “Dimension” to Date and the “Metric” to your chosen value.
   
   
3. Table: A table is excellent for detailed data, like your top-performing pages. Add a table chart and configure dimensions (e.g., Page Title) and metrics (e.g., Pageviews).

You can drag these components to arrange them logically on your canvas.

Image: How to Add a Graph to a Looker Report

Step 4: Style, Share, and Explore

Lastly, you can also try adjusting the style of your report and then chart/explore the data visualization.

 

• Styling: You can customize any chart to customize it. Simply use the “Style” tab on the right to change colors, fonts, and backgrounds to match your brand!

 

• Interactivity: This is how you make your dashboard interactive – from the toolbar, insert a “Date Range Control” or “Filter Control.” This will allow your visualization’s viewers to change the date range or filter the data themselves.

 

• Sharing: Click the “Share” button in the top-right corner. You can send a viewable link, grant edit access to teammates, or even embed the dashboard on a website.

Pro Tip: Don’t start from scratch every time. Instead, save time by exploring the “Template Gallery” (accessible from the main Looker Studio homepage) for pre-built report designs. You can then customize these templates with your own data.

Looker Studio Pricing Guide

Finally, let’s talk about brass tacks – how much will using Looker Studio cost you?

The simple answer – nothing, the basic version is absolutely free. But if you want to create more complex visualizations with a lot of data, Looker Studio Pro might be worth the cost.

Let me walk you through the pricing:

Looker Studio (Free Version)

The standard version of Looker Studio is completely free to use.

And this isn’t a limited-time trial – it’s a fully functional tool that will probably meet all your needs if you’re an individual, small business, or even agency user.

Here’s what the free version includes:

• All core visualization and dashboard-building features.
• Connectivity to hundreds of data sources, including all Google connectors.
• Unlimited report creation and editing.
• Basic sharing and collaboration capabilities.
• Full access to the template gallery.

As you can see, the free version provides more than enough power to create interactive reports without any cost!

Looker Studio Pro (Paid Version)

Looker Studio Pro is the enterprise-grade tier – priced at $9 per user, per project, per month (you’ll be billed through a Google Cloud account).

It’s designed for organizations that require three things – governance, security, and support.

Let me walk you through some situations when you can consider paying for the Pro version:

• You need advanced Identity and Access Management (IAM) via Google Cloud.
• You want dedicated technical support and service level agreements (SLAs).
• You’re working with a large team and need centralized administrative controls.
• You require asset management and sharing permissions for a large org.

My Suggestion: Start with the free version. It’s powerful enough for most use cases. You only need to consider Looker Studio Pro if your organization has specific enterprise-level requirements for security, administration, or support.

Augmented Tech Labs: Your Looker Data Visualization Specialist

As we’ve seen throughout this post, Looker Studio can empower you to transform raw data into clear, actionable dashboards. Its free accessibility and intuitive interface can help you move from scattered spreadsheets to unified reporting almost immediately!

But there’s a crucial difference between building reports and driving business impact! While anyone can create basic charts, unlocking Looker Studio’s full potential requires strategic expertise.

The real value emerges when you need to:

• Aggregate and clean data from several sources to calculate true marketing ROI.
• Build custom calculated fields that reveal customer behaviour patterns.
• Design executive-level dashboards that highlight all major KPIs.
• Scale your analytics across departments while maintaining governance and control.

This is where we at Augmented Tech Labs come in to make an actual difference to your data visualization operations!

Image: Why Choose Augmented Tech Labs for Looker Data Visualization?

We don’t just build dashboards – we engineer data solutions that drive better decisions.

While your team might need months learning advanced data blending and visualization best practices, we deliver production-ready analytics in weeks.

And if you’re still not sure whether we can actually help you out, just schedule a free analytics assessment with our team!

We’ll review your current data stack and show you exactly how to transform Looker Studio from a reporting tool into a competitive advantage…

What is Looker Studio: FAQs

1. What is a Looker Studio dashboard?

A Looker Studio dashboard is an interactive report that connects to live data sources, transforming raw numbers into visual charts and graphs. It provides a single, real-time view of your key business metrics for smarter decision-making.

 

2. What are the main benefits of Looker Studio?

The primary benefits of Looker Studio include its free cost, user-friendly drag-and-drop interface, and ability to create a single source of truth by blending data from over 1,200 sources into clear, shareable reports.

 

3. How to use Looker Studio?

To start using Looker Studio, sign in with a Google account and connect a data source like Google Analytics. Then, use the drag-and-drop editor to add charts. Once you’ve created a chart, you can style and share your interactive Looker Studio dashboard with teammates or clients.

 

4. When should I hire a data visualization specialist for Looker Studio?

I suggest hiring a data visualization specialist for Looker if/when you need to build complex, calculated fields based on multiple data sources for advanced insights, or design scalable, executive-level dashboards that drive specific business outcomes beyond basic reporting. A visualization expert will offer immediate expertise and results that your internal team might need a lot of time and money to deliver.

 

5. Which Looker Studio features are most important for agencies?

Key Looker Studio features for agencies are white-label branding options, template galleries for speed, and interactive filter controls. These allow you to deliver professional, client-specific dashboards that tell a compelling data story.

Microsoft’s Power BI is one of the best business intelligence tools on the market.

But if you need:

• Pixel-perfect reports. 
• Real-time data processing capabilities.
• A cost-effective + scalable BI platform.

There are better options out there!

At Augmented Systems, we’ve helped a lot of clients find their ideal Power BI alternative that aligns perfectly with their use case.

And in this article, that’s what we’re going to help you do as well!

We’ll break down 10 Power BI alternatives that double up as data visualization tools and software, so you can choose one that works for you!

Let’s dive in!

Power BI Alternatives: Table of Contents

• TL;DR: Top 5 Power BI Alternatives
• Power BI Alternatives: Table of Comparison
• List of 10 Top Power BI Alternatives in 2025
• Final Verdict: Which Power BI Alternative is the Best?
• Power BI Alternatives: FAQs

TL;DR: Top 5 Power BI Alternatives

In a hurry? I’ve got you covered – here’s a quick breakdown of the 5 best Power BI alternatives based on the most common use cases:

Best Enterprise-Grade Alternative – Tableau

The market leader in visualization capabilities, Tableau can handle massive datasets pretty well and also offers robust governance features. Ideal for large corporations needing deep, exploratory analysis!

Best Open-Source Alternative: Apache Superset

Completely free, highly scalable, and customizable. Designed for tech companies with strong engineering teams that want full control without any licensing fees.

Best AI-First Alternative: Qlik Sense

Qlik’s associative analytics engine and AI-powered Insight Advisor help you automate insight discovery through natural-language queries and relationship-indexing. This means you can explore data beyond set dashboard structures and uncover hidden trends!

Best Affordable Alternative: Zoho Analytics

Zoho offers a powerful, forever-free plan and extremely competitive pricing. On top of this, it provides incredible value for SMBs and startups needing robust data visualization tools without the enterprise cost.

Best White-Label / Embed Alternative: Sisense

Sisense is one of the best API-first business intelligence tools – it offers industry-leading capabilities for embedding interactive, white-labeled analytics directly into customer-facing applications and software products!

Power BI Alternatives: Table of Comparison

Here’s a quick summary of our detailed comparison of the top 10 Power BI alternatives on the market:

 

List of 10 Top Power BI Alternatives in 2025

As promised, here’s our list of the top Power BI competitors and alternatives. We’ve included a good range of platforms, including enterprise-grade data visualization software and BI-first tools that also offer visualization capabilities.

Here’s how the list stacks up:

1. Tableau

2. Qlik Sense

3. Looker (Google Cloud Core)

4. Domo

5. Sigma Computing

6. Sisense

7. Zoho Analytics

8. SAP Analytics Cloud

9. Metabase

10. Apache Superset

1. Tableau

First on my list of Power BI alternatives is Tableau – the undisputed market leader in the data visualization segment.

It helps you convert complex data into vivid visualizations – from what we’ve seen, no other BI tool comes close to Tableau in terms of its data visualization capabilities.

It’s also very good for creating executive dashboards that help you track all your KPIs in one accessible place.

Best for: Large enterprises and data analysts who require deep, exploratory analysis and powerful + flexible visualization capabilities.

Standout Features of Tableau

• Drag-and-Drop Interface: One of the best things about Tableau is that you don’t need any background in coding to create visualizations. All you have to do is drag and drop fields, rows, or columns into its interface, and it’ll create interactive dashboards and visualizations for you.
• Extensive Data Connectivity: Whether you use a CRM like Salesforce or a data warehouse like Snowflake or one of hundreds of other sources, Tableau’s expansive range of connectors helps you integrate it with your existing tech stack.
• Advanced Visualizations: Tableau will never try to fit your data into a limited range of graphs – it has a wide range of visualizations, from geo maps to scatter plots to customized bubble charts – to help you tell the perfect story with your data. 

 

Also Read: Head-to-Head Comparison Between Power BI vs Tableau

Pros of Tableau

• Extensive data visualization capabilities.
• User-friendly tool, ideal for beginners and non-technical users.
• Strong community with a wide range of resources.
• Handles large datasets pretty efficiently.
• Highly suitable for exploratory data analysis.

Cons of Tableau

• As expensive as Power BI, especially for enterprise deployment via Server/Cloud.
• Compared to some other Power BI alternatives, its advanced features are hard to learn.
• You might need to use Tableau Prep to prepare your data for analysis. 

Tableau Pricing

• Tableau Creator: $75/user/month (includes Desktop + Prep + Server/Cloud license).
• Tableau Explorer: $42/user/month (for exploring and interacting with content).
• Tableau Viewer: $15/user/month (for viewing pre-built dashboards).

2. Qlik Sense

Qlik Sense is an AI-powered BI platform that is built on a unique associative analytics engine.

Its core strength is that it can index the existing relationships in your data, which means your team can freely explore information and uncover hidden insights without being limited to pre-defined paths.

Best for: Enterprises and power users who value data discovery and unguided exploration over strictly pre-built dashboards.

Standout Features of Qlik Sense

• Associative Analytics Engine: With Qlik, getting insights from your data is more like a conversation. Since it doesn’t limit you to a pre-defined structure, you can use it to explore relationships between your data in different directions.
• AI-Powered Smart Data Discovery: One of Qlik’s most powerful features is its ability to create dashboards and charts in response to natural language queries like, “Why are sales down this quarter?” Alternatively, it can also automatically generate dashboards directly based on your data.
• Powerful Data Migration & Modeling: You can integrate Qlik with on-site or cloud data sources. So, if you need a data visualization software that can pull up data from a wide range of sources, Qlik might be worth a shot. 

Pros of Qlik Sense

• Industry-leading data discovery and associative modeling capabilities.
• Robust governance + scalability for enterprises.
• In-memory engine that doesn’t lag with large datasets.

Cons of Qlik Sense

• The associative model can be conceptually different for new users.
• Can be more expensive than some competitors, especially when you want to scale.
• Requires careful data modeling for optimal performance.

Qlik Sense Pricing

• Business: $30/user/month (Standard SaaS plan)
• Enterprise SaaS: Custom pricing (full enterprise features)
• Enterprise Client-Managed: Custom pricing (on-premise deployment)

3. Looker (Google Cloud Core)

Looker is Google’s native business intelligence platform.

What’s unique about it is that it is more than just a data visualization tool – it is based on a proprietary modeling language called LookML.

It thus acts as a single source of truth for your enterprise data.

Best for: Tech-savvy companies, especially those using Google BigQuery, that need a governed, consistent metrics layer and powerful embedded analytics.

Standout Features of Looker

• LookML: Looker defines, measures, and calculates all your data, metrics, and calculations in one place through a native modeling language. This means all users, from employees to executives, see the same, accurate, and consistent data.
• Deep Google BigQuery Integration: If you need real-time analysis for massive datasets, Looker might be one of the best tools on the market. That’s because it has a very tight native integration with BigQuery, Google’s native data warehouse.
• Power API & Embedded Analytics: One of Looker’s core strengths features is that it was built with an API-first approach in mind. That means you can embed it in interactive dashboards, customer-facing applications, and enterprise workflows, and more!

Pros of Looker

• Ideal for creating a centralized, governed “single source of truth.”
• Highly suited to companies that are already using Google’s Cloud ecosystem.
• Very powerful embed capabilities for analytics use cases.

Cons of Looker

• You’ll need SQL knowledge or dedicated developers to build the LookML models.
• Doesn’t offer the best drag-and-drop analysis or capabilities for business users.
• Pricing is enterprise-oriented, so it can be both complex and expensive. 

Looker Pricing

Custom pricing based on platform edition (Standard, Enterprise, Embed) and usage. However, from what we’ve seen, you can expect to pay $3,000-$5,000/month for its full suite of capabilities.

4. Domo

Domo makes my list of Power BI alternatives as one of the best data visualization and analysis tools on the market.

It is an enterprise-grade, API-first tool that you can integrate into enterprise workflows, apps, websites, data warehouses, and more.

Some of its core strengths are real-time data delivery, strong communication capabilities, and integration features.

Best for: Organizations that need to aggregate data from countless SaaS applications and require real-time insights and alerts on operational data.

Standout Features of Domo

• Massive Connector Library: If your data is scattered over multiple sources like warehouses, CRMs, and SaaS apps, Domo will bring them all in one place through its 1,000+ native data connectors.
• Real-Time Dashboards & Alerts: One thing we really like about Domo is that its data updates in real-time, so you don’t need to wait for scheduled refreshes to get a clear insight into your data. It also sends you notifications when key thresholds are breached.
• Collaboration Capabilities: Domo excels at bringing together not just data, but also people. Users can tag each other on visuals or dashboards, comment on them, and even share insights directly on data cards + dashboards. 

 

Also Read: Domo vs Power BI: Which Business Intelligence Tool Should You Choose?

Pros of Domo

• Market leader in terms of the number of data connectors.
• Very strong mobile experience and real-time capabilities.
• All-in-one platform which eliminates the need to use + pay for multiple tools. 

Cons of Domo

• Definitely one of the more expensive Power BI alternatives on the market.
• The vast array of features can be overwhelming for new users.
• Less customizable for deep, complex visualizations compared to Tableau.

Domo Pricing

Custom pricing based on the no. of users, data refresh rates, and features you need. From what we’ve seen, it starts in the low thousands per month for a small team.

5. Sigma Computing

If you’re looking for a Power BI alternative with a spreadsheet-like user interface, Sigma Computing might be your best bet!

It is designed to connect directly with data warehouses and handle datasets with billions of rows and columns without moving data or requiring coding/engineering expertise.

Best for: Companies with a modern cloud data warehouse stack that want to empower business users (in Finance, Marketing, etc.) to do self-serve analysis on live data.

Standout Features of Sigma Computing

• Spreadsheet-like Interface: If you’ve got a marketing or finance team that’s already familiar with Excel or Sheets, switching to Sigma will feel like a massive upgrade without a change in the UI to them. Plus, with its NLP-based queries, you can get insights into your data without any coding.
• Live Connection to Cloud-Warehouses: Sigma eliminates the hassle of importing/exporting data to/from different tools. It runs queries directly on your cloud warehouse-based dataset. This means you’ll never get insights on outdated/stale data!
• Governance + Control: Sigma helps you comply with regulations and maintain complete control over your dataset. While it allows users to explore datasets, only admins have full control over who has access to which dataset!

Pros of Sigma Computing

• Very easy to learn for users familiar with spreadsheets.
• Increases efficiency since you never have to move data around to get insights. 
• Reduces the burden on data teams for ad-hoc report requests.

Cons of Sigma Computing

• Highly dependent on the performance + cost of your cloud data warehouse.
• Less capable for highly complex, custom visualizations compared to dedicated tools.

Sigma Computing Pricing

Custom pricing based on a per-user subscription model.

6. Sisense

Sisense is one of the best Power BI competitors on the market for handling large, complex datasets.

It also has a strong, embed-first design and can import data from multiple sources. What’s unique about Sisense is that it actually optimizes and enhances the performance of large-scale and complex datasets through its proprietary chip technology.

Standout Features of Sisense

• Embed Analytics Capabilities: Sisense is one of the BI tools on the market for white-label analytics capabilities. With its robust APIs and SDKs, you can integrate interactive dashboards and analytics straight to your customer applications.
• In-Chip Tech: Sisense’s proprietary chip tech helps you optimize and accelerate the analysis of large, complex datasets by leveraging your CPU’s cache. This is a key reason why Sisens remains responsive and fast even when working with billions of rows of data.
• Elasticube Data Modeling: Elasticube is Sisense’s semantic layer – your programmers can use it to create high-performance models that bring together data from numerous sources. 

Pros of Sisense

• Highly customizable dashboards with drag-and-drop capabilities.
• Offers AI-driven analytics in response to natural-language queries.
• Highly scalable for enterprise deployments.

Cons of Sisense

• Can be complex to set up and administer without technical expertise.
• Might be too expensive for startups, solopreneurs, or SMEs.
• The UI is not as slick and modern as other Power BI competitors. 

Sisense Pricing

Custom pricing based on deployment type (cloud or on-premise), no. of users, and data volume.

7. Zoho Analytics

Zoho Analytics is one of the most user-friendly Power BI alternatives on the market.

Its strong data visualization capabilities and integration with the Zoho ecosystem also make it a very attractive option for enterprises with a diverse range of users.

However, you can also integrate Zoho Analytics with a wide range of apps + third-party resources, so it might be worth a shot even if you’re not currently using any other Zoho products!

Best for: Small to medium-sized businesses (especially those already using Zoho products) looking for a powerful and affordable BI tool.

Standout Features of Zoho Analytics

• Zia, the AI Assistant: You can use natural language queries like, “What was the state of sales in the last two quarters?” Zoho’s AI assistant, Zia, will automatically generate relevant reports + answers, along with insights and forecasts.
• Deep Zoho Integration: Zoho is best known for its CRM, books, and helpdesk capabilities, all of which integrate with Zoho Analytics. You can connect Analytics with these apps, and it will automatically import data for report building and other data visualization tasks.
• Affordable + Flexible Pricing: Zoho Analytics comes with a forever-free plan, while still offering enterprise-grade data visualization and analytics features. It’s thus one of the best options for startups, solopreneurs, and SMBs.

Pros of Zoho Analytics

• Very easy to use, even for non-technical users.
• Users can collaborate on data cards, visualizations, and reports in real-time.
• Offers a decent mobile experience through the Zoho Analytics app. 

Cons of Zoho Analytics

• You might face performance lags with large datasets.
• The analytics capabilities are less advanced compared to enterprise-grade tools.

Zoho Analytics Pricing

• Basic: $24/month for 2 users.
• Standard: $48/month for 5 users.
• Premium: $115/month for 15 users.
• Enterprise: $455/month for 50 users.

Also offers a forever-free plan with limited capabilities.

 

8. SAP Analytics Cloud

SAP Analytics Cloud, or SAC, is an all-in-one cloud platform that brings together planning, analytics, and predictive modeling.

Simply put, it’s the native analytics solution for the SAP ecosystem, and therefore also offers very strong integration with SAP’s enterprise-grade planning applications.

Best for: Large enterprises that are heavily invested in the SAP ecosystem and need integrated planning and analytics.

Standout Features of SAP Analytics Cloud

• Unified Planning & Analysis: You can use SAC to bring together business intelligence with predictive planning and analytics to break down data silos. For example, you can compare actuals vs plans and budgets without switching workflows or screens.
• Predictive Analytics & Machine Learning: Helps you run scenarios, detect anomalies, and generate forecasts, without requiring you to have any advanced data analysis skills. Its AI does all the heavy lifting for you – all you have to do is feed it natural language queries.
• SAP Integration: Integrates seamlessly with other SAP applications like S/4HANA, BW, and SuccessFactors. This means it runs analysis on live transactional data and plans based on real-time information, making it the outstanding choice for orgs already using SAP apps. 

Pros of SAP Analytics Cloud

• Helps you create personalized & customized dashboards.
• Good mobile experience through a dedicated app.
• Strong enterprise-grade security and governance.

Cons of SAP Analytics Cloud

• The pricing might be too expensive for startups + solopreneurs. 
• Steep learning curve for non-SAP users.
• The user experience is improving, but it’s still more “corporate” and less “agile”.

SAP Analytics Cloud Pricing

Custom pricing based on a subscription model. Typically sold in blocks of users – BI, Planning, Predictive.

9. Metabase

Metabase makes my list of Power BI competitors as an open-source, lightweight business intelligence software.

If you’re looking for a data visualization tool that lets you or your team ask queries about your data without writing code, Metabase might be one of the best non-expensive options on the market.

And if you’re familiar with SQL, you can be a power user of Metabase and leverage its full capabilities!

Best for: Startups and SMBs with limited budgets that need a simple, effective, and open-source tool for basic internal reporting and dashboards.

Standout Features of Metabase

• Ease of Use + Setup: You can install Metabase and connect your database with it in as little as 10-15 minutes. Plus, its intuitive interface is designed to help non-technical users create simple data queries and dashboards almost immediately.
• Open-Source Core: Offers complete transparency, control, and access to its data and application. So, it’s ideal for anyone operating with a limited budget and/or tech-savvy teams.
• Simple Share & Embed Features: Metabase makes it very easy for you to share questions, visuals, and reports. Plus, you can also embed them in other portals, websites, and apps with minimal effort. 

Pros of Metabase

• Integrates with a wide range of SQL databases.
• You can build complex queries very easily with its click-and-point interface.
• Metabase sends you scheduled alerts or notifications for changes in your datasets.

Cons of Metabase

• Not the best option for very large-scale enterprise deployments with complex needs.
• Fewer advanced visualization and data modeling options.
• Performance depends heavily on the database you’re using.

Metabase Pricing

• Open Source: Free (self-hosted).
• Pro (Cloud): Starting at $85/month (hosted by Metabase).
• Enterprise: Custom pricing for advanced features & support (self-hosted).
  

10. Apache Superset

Apache Superset is an enterprise-grade open-source Power BI alternative.

It’s designed to handle data at the petabyte level, while you can use it either as a standalone visual interface for your data or an embedded solution in apps/workflows/websites.

However, you might have to work with a data visualization services provider to make the most of its features.

Best for: Tech companies with strong engineering teams that want a free, scalable, and customizable platform they can fully control and embed.

Standout Features of Apache Superset

• Completely Free, Open-Source: It’s rare for an enterprise-grade tool to be open source, but that’s exactly what Apache Superset brings to the table. It’s built for modern, scalable, and cloud-first data environments.
• Powerful SQL Visualization Capabilities: Comes with a rich SQL editor you can use for data exploration. Plus, its data visualization library helps you create a wide range of charts, tables, and dashboards through code.
• Extensive Database Support: Through its SQLAlchemy integration, it supports a vast number of SQL-based databases out of the box. Simply put, Apache integrates with almost any modern database or data source. 

Pros of Apache Superset

• Highly scalable and can handle massive datasets with billions of data points.
• Completely free and open-source with a very active community.
• The code-based visual editor is extremely powerful.

Cons of Apache Superset

• You’ll need technical expertise to deploy, manage, and maintain Apache Superset.
• Lacks official enterprise support unless you use a commercial provider.

Apache Superset Pricing

Pricing: Free (Open-Source). Commercial support and managed services available from providers like Augmented Tech Labs.

Final Verdict: Which Power BI Alternative is the Best?

Through this blog, we’ve walked you through the top 10 Power BI alternatives on the market.

We explored the best enterprise-grade tools like Looker and Sigma, open-source platforms like Metabase and Apache, and embed-first Power BI alternatives like Domo and Sisense.

So, which one of them is the best?

As veteran data visualization services providers, our answer is that it depends on your use case!

Simply put, whichever tool offers the capabilities that you need – such as compliance, governance, integration, ability to handle complex datasets – is the one you should go with.

To make an informed decision, we suggest making a checklist of all the features you need, and only selecting that tool which ticks all the boxes.

And if you’re struggling to choose the right one for your enterprise, don’t worry – just reach out to our database engineers at Augmented Systems…

We’ll understand your requirements, run a quick audit of your existing tech-stack, and give you a tailored assessment of which Power BI alternative is right for you!

All you need to do is tell us about your priorities, objectives, and current challenges, and we’ll help you pick the top data visualization tool on the market.

 

Power BI Alternatives: FAQs

1. Why should you look for Power BI alternatives?

While Power BI is a decent BI tool for Microsoft-centric ecosystems, it has several limitations:

• Unpredictable pricing model, which makes scaling challenging + costly.
• Its real-time analytics capabilities aren’t the best in the market. 
• The learning curve is steep + it doesn’t offer advanced analytics, which makes learning Power BI a pretty expensive investment.

Compared to Power BI, there are several alternatives that offer better visualization, embed + API, and analytics capabilities.

2. What is the best open-source data visualization software?

In our experience, Apache Superset and Metabase are two of the best open-source power BI alternatives and data visualization software. Superset is more powerful and scalable for engineering teams, while Metabase is easier to set up and use for non-technical teams seeking simple internal dashboards.

3. Which alternative is best for a company that uses Google BigQuery?

Looker (Google Cloud Core) is the native and optimal choice. It is built for and deeply integrated with BigQuery, offering unparalleled performance, consistency, and governance for data within the Google Cloud Platform.

4. Are there any good free data visualization tools?

Yes – Zoho Analytics comes with a pretty good free plan, while Metabase and Apache Superset are completely free (if you self-host the open-source versions or work with a data visualization services provider). These are great for startups and small teams with limited budgets.

 

5. What is the difference between data visualization software and business intelligence tools?

These terms are often used interchangeably, but there’s a slight difference between them. Data visualization software is a subset of business intelligence tools, while BI tools include a wider range of capabilities like data preparation, warehousing, reporting, and advanced analytics, while visualization focuses specifically on the graphical representation of data. Usually, you need both to create a robust BI ecosystem.

6. When should a company consider using embedded analytics?

You should consider embedded analytics (using tools like Sisense or Looker) if you want to get data insights directly within your own software application or customer portal. They’ll help you enhance your product’s value and create a seamless user experience.

7. I need to connect to many SaaS apps. Which tool is best?

Domo is the standout choice for connecting data analytics with SaaS apps. It offers you a library of over 1,000 pre-built connectors, which you can use to unify data from cloud services, databases, and applications.

8. What does “associative analytics” mean in Qlik Sense?

Unlike traditional tools that follow a predefined query path, Qlik Sense’s associative engine indexes all relationships within your data. So, Sense lets you explore information freely in any direction, with the interface visually highlighting related data and dimming unrelated data, leading to unexpected insights.

9. Why/when should you work with a data visualization services provider?

You might want to work with an experienced data visualization services providers (like Augmented Tech Labs) if you:

• Don’t have or don’t want to hire an in-house expertise to select, implement, and customize a BI platform.
• Need to build complex custom dashboards.
• Want to integrate analytics into existing workflows seamlessly.

Database management and data visualization services providers like us help you make the most of both open-source and licensed business intelligence platforms.

10. Is Microsoft Excel still a valid BI tool?

Yes, MS Excel is still a valid BI tool for specific use cases. With Power Query and Power Pivot, you can use Excel for individual, ad-hoc analysis and data manipulation. However, it lacks the centralized governance, security, and collaboration features of a full BI platform and is not suitable for enterprise-wide reporting.

Tableau connectors can help you bridge the gap between your data infrastructure and Tableau’s data visualization capabilities.

But which connector should you use – a native, a partner-built or a third-party?

The answer usually depends on the kind of data you want to extract and the system you use to store your data.

In this blog, I’m going to walk you through the 15 best Tableau connectors that you can use to seamlessly import your data into Tableau without any hassle.

I’ve included 5 tools under each category – native, partner-created, and third-party – so you can choose the right one that fits with your tech stack.

Let’s get started!

Top 15 Tableau Connectors: Table of Contents

• What are Tableau Connectors?
• 15 Best Tableau Connectors You Need to Know About

  – Best Native Connectors

  – Best Partner Connectors

  – Best Third-Party Connectors

• Connect with Tableau and Start Visualizing Your Data
• Tableau Connectors: FAQs

What are Tableau Connectors?

Tableau connectors are software components, drivers, and plugins that translate data from a source’s specific protocol into a language that Tableau can understand.

These connectors use two primary modes to help you integrate your data with Tableau:

• They import data from multiple sources, such as data warehouses, web apps, cloud services, CRM software, and more, into Tableau.
• They generate and send queries in SQL or other languages to the source system, thus setting up a live connection between a data source and Tableau.

Simply put, a connector will ensure that you can skip the first phase of data visualization and analysis: manually importing large files to your Tableau interface.

As a result, you can access all your data in a single place – Tableau – when you need to analyze or visaulize.

That’s why understanding how these connectors work is one of the most critical aspects of learning how to use Tableau.

What are the 3 Types of Tableau Connectors?

There are three types of connectors that you can use to integrate data with Tableau:

• Native Tableau Connectors: Developed, maintained, and bundled directly by Tableau, these connectors are available out-of-the-box in Tableau Desktop. 
• Partner-Built Tableau Connectors: These are built by Tableau’s tech partners using the Tableau Connector SDK. They are typically found on Tableau Exchange. 
• Third-Party Tableau Connectors: Third-party connectors are built by vendors outside of Tableau’s official partnership program. 

This classification will help you understand three things: where you can get the connector, how it’ll be supported, and the level of integration you can expect.

 

Once you know how these connectors operate, you can easily create reports and interactive Tableau dashboards.

15 Best Tableau Connectors You Need to Know About

Finally, let’s dive in and explore the 15 best connectors that you can use to integrate your data with Tableau.

Best Native Connectors

First, let’s take a look at the best connectors that Tableau itself has built and continues to maintain: 

1. Azure Data Lake Tableau Connector

If you use Azure Data Lake Storage Gen2 as your data storage and warehousing solution, the Azure Data Lake Tableau Connector is how you can connect Tableau to your data.

You can use it to connect your data in two ways:

• Live Connection: The connector generates and sends queries to Azure, so you get direct access to the most current data from the data lake.
  
• Data Extract: You can also import a snapshot of the data into Tableau’s high-performance engine for optimized analysis, even when offline.

One of the key features of this integration with the Azure ecosystem is that it uses OAuth with Azure Active Directory for secure, modern authentication, letting users sign in with their existing Azure accounts.

Plus, the Azure Tableau connector is designed for self-service – this means you can quickly connect to files (like CSVs) in the data lake and start analysis without converting, moving, or preparing the data in a different format.

Azure is one data source for which Power BI also has many data connectors. So, if you’re using Azure, check out my blog on Tableau vs Power BI to find out which one offers better connectivity.

2. Amazon S3 Tableau Connector

Next up, we have the Amazon S3 Tableau Connector.

It helps directly connect to and analyze data stored in Amazon Simple Storage Service (S3) buckets without moving it to another system.

Let me quickly walk you through its most important features through a table:

Here’s how this connector works:

After providing your AWS credentials (Access Key ID and Secret Access Key), bucket name, and region, you can browse and select the files you wish to analyze.

What I really like about this connector is the support it offers for data unions and joins. You can combine multiple files of the same type within a bucket for a more comprehensive dataset view.

Plus, through a live connection with Parquet files, you get extract-like performance for dashboards. So, you can ensure that new data is reflected automatically without waiting for scheduled updates.

There are also three limitations you might want to consider before using this connector:

• Authentication: Only supports long-term AWS IAM User access keys (key ID and secret key); temporary session tokens are not supported.
• Publishing: Workbooks and data sources must be published to Tableau Server using the “Embedded password” option.
• File Size Limits: Individual files are limited to 15 GB, and Excel files should not exceed approximately 100 MB for performance reasons.

And if you get stuck with any of these problems, I suggest reaching out to reliable data visualization consultants. They can help you create tailored solutions to overcome these challenges of the Amazon S3 Tableau connector.

3. Google BigQuery Tableau Connector

Third on my list is the Google BigQuery Tableau Connector.

It’s a native tool that bridges Tableau with Google’s powerful cloud data warehouse.

You can use it to directly query and visualize massive datasets stored in BigQuery without moving them to Tableau.

The best part about this connector is its newer  (JDBC) connector is that it has three enterprise-grade functionalities:

• Cross-Project Joins: You can join tables from different BigQuery projects within a single Tableau data model.
• Large Result Datasets: Handles large queries by automatically creating temporary staging tables in BigQuery.
• Initial SQL: Supports executing Initial SQL commands right from the beginning of a live connection.

I highly recommend using this version of the connector for its advanced capabilities.

With it, you can either establish a live connection for real-time analysis on the freshest data or create a high-performance data extract for optimized dashboard speed.

Another major advantage of this connector is its deep integration with the Google Cloud ecosystem, which uses OAuth for secure and streamlined authentication with your Google account.

4. LinkedIn Sales Navigator Tableau Connector

Next, we have the LinkedIn Sales Navigator Tableau Connector.

It’s a native tool designed for sales teams to help them pull valuable product usage data directly into Tableau for analysis.

More specifically, it allows managers with a Sales Navigator Enterprise plan to track team activity metrics, such as searches performed, InMails sent, and profile views.

You can thus use it to transform raw usage data into actionable insights on sales engagement!

However, it is crucial to note that this connector has been officially deprecated as of Tableau 2023.1 and is slated for retirement.

So, while existing workbooks may continue to function for a time, I recommend not using this connector for new projects.

Tableau has indicated that a replacement connector is in development, but for now, I suggest seeking alternative methods for integrating this data. You can also use data visualization services to create a custom workaround for enterprise operations.

5. Salesforce CRM Tableau Connector

Last on my list of Tableau’s native connectors is the Salesforce CRM Tableau Connector.

It creates a direct connection between Tableau and your Salesforce data.

You can use it to analyze and visualize critical CRM data, be it from Sales Cloud, Service Cloud, and Marketing Cloud, without complex data exports.

Here’s how it works: the connector will pull data from Salesforce into Tableau as a data extract, which is then optimized for high-performance analysis and dashboarding.

One of its key features is that it can perform cross-database joins, enabling you to combine your Salesforce data with info/data from other sources.

 

It thus functions like a data warehouse within a single, unified data model.

To use it, you must authenticate via OAuth and enable API access on your Salesforce account.

You should also note that this connector operates primarily with data extracts rather than live connections for core CRM objects. So, while it ensures performance, you’ll have to update the data manually to stay current.

For a quick start, I suggest using pre-built Tableau Accelerators – these are dashboard templates designed specifically for common Salesforce analytics scenarios like sales pipeline inspection.

Best Partner-Built Tableau Connectors

Partner-built connectors are designed by Tableau’s tech partners. They function as seamlessly as Tableau’s native connectors. Let me walk you through the best of them:

6. Rollstack Tableau Connector

The Rollstack Tableau Connector is a partner-built tool.

It’s designed to help you automate the process of embedding live Tableau dashboards and visualizations into business documents like PowerPoint, Google Slides, and Word.

Thus, its primary purpose is to help you eliminate complex exports into business documents.

You can use it to connect your Tableau account to Rollstack, select specific dashboards and visualizations for your reports.

One thing I really like about this Tableau connector is that you can schedule automatic data updates, which means the presentations and documents you’ve created always reflect the most current data from Tableau without any manual intervention!

It also supports the use of templates, so you consistently and quickly create branded reports for different departments or clients.

Plus, you can also control the version of your reports and manage archives of past reports.

The connector is particularly valuable for automating recurring reports such as Quarterly Business Reviews (QBRs), financial reports, and client presentations while saving time and reducing manual errors.

Another thing I’ve noticed is that its recent updates have added support for Tableau Custom Views, which means you can create presentations that automatically include saved states of interactions like filters and sorts.

7. dbt Semantic Layer Tableau Connector

The dbt Semantic Layer Tableau Connector is designed by dbt Cloud to provide a live connection from Tableau to the centrally defined business metrics of your projects.

It ensures that everyone in your organization uses the same trusted, consistent metric definitions directly within Tableau.

Simply put, you don’t need to rebuild the logic of your tables and their relationships manually.

To use the connector, you need a dbt Cloud Team or Enterprise account with dbt v1.6 or higher and the Semantic Layer configured.

Once you’ve downloaded the connector (a .taco file) from the Tableau Exchange and the required JDBC driver, place them in the correct folders on your machine and restart Tableau.

You can then connect using three things: your dbt Cloud host, Environment ID, and a service token.

One of its key features is that you can access the “ALL” data source, which brings all available metrics and dimensions from your dbt project into your Tableau interface.

However, this connector only supports live connections – data extracts are not possible. I suggest reaching out to a data visualization consultant to create a workaround to this problem.

8. Ocient JDBC Tableau Connector

Next up, we have the Ocient JDBC Tableau Connector:

It allows you to connect Tableau to Ocient’s SQL node by providing a database host, port, database name, and user credentials.

This connector is particularly suited to speeding up querying for pentabyte-scale data. This is primarily because Ocient’s architecture uses massively parallel processing to execute queries on hyperscale datasets up to 100x faster than alternatives.

To use the connector, you need to install two files:

• First, download the Ocient JDBC Driver (a .jar file) and place it in the “Drivers” directory of your Tableau installation. 
• Next, download the Ocient Tableau Connector file (a .taco file) and move it to the “Connectors” folder within your “My Tableau Repository”. 

Then, restart your Tableau app and select “Ocient JDBC” from Tableau’s list of connectors.

Since this connector can be pretty challenging to connect and use, I suggest working with experienced data visualization services providers to make the most of it.

9. MongoDB SQL Tableau Connector

The MongoDB SQL Interface Tableau Connector is a partner-built connector that you can use to establish a direct SQL connection from Tableau to live data in your MongoDB database.

This integration is particularly beneficial for analysts as it allows them to use their SQL skills to query MongoDB’s document data.

As a result, your business analysis team can get faster insights without building complex ETL pipelines.

To use the connector, you need a MongoDB deployment (version 6.0 or higher) and must download the official “Tableau Connector for MongoDB” (a .taco file) + the required JDBC driver from the MongoDB website.

Once you’ve placed these files in the correct Tableau folders and restarted the application, you can connect using your MongoDB connection string and credentials.

One of my favorite features of this Tableau connector is its dynamic schema computation. It automatically and accurately maps your MongoDB collections to a SQL-queryable format, eliminating the need for manual schema files.

Plus, this connector uses MongoSQL, a SQL-92 compatible dialect, which supports complex operations like joins and aggregations.

Lastly, I also want to point out that this new connector is the strategic replacement for the legacy BI Connector, which is scheduled for end-of-life in September 2026.

10. Yellobrick Tableau Connector

Last on my list of the best partner-built Tableau connectors is the Yellowbrick integration.

This connector is a crucial part of Yellowbrick’s strategy to build a robust partner ecosystem. You can use it to combine Yellowbrick’s hybrid cloud technology with Tableau’s analytics capabilities to improve data analytics with minimal operational overhead.

It provides native, high-performance connectivity from Tableau to the Yellowbrick data warehouse, perfect for users who want to analyze large datasets at high speed right within their Tableau environment.

This connector, validated by Tableau and available for both Tableau Desktop and Tableau Server, is tuned for optimal performance and offers a seamless user experience that looks and feels like a native Tableau connector.

What I like about this connector is that the installation is straightforward: just download the connector file (.taco) and place it in the “My Tableau Repository/Connectors” folder.

Once this is done, you’ll see the Yellowbrick connector in the Connect pane within your Tableau interface.

Best Third-Party Tableau Connectors

Lastly, we have the category of third-party Tableau connectors, built by orgs and companies to fill the gaps in the existing connector database. Here are the five best ones that you need to know about:

11. Alpha Serve Tableau Connectors

First up, we have Alpha Serve: if you use Jira, Zendesk, Shopify, and other such popular business apps, it’s the perfect connector for you.

It offers you a suite of enterprise-grade Tableau connectors that you can use to import data from such business apps.

Crucially, these connectors function as no-code solutions – which means you can create data sources and generate a URL link within the source application.

This is then connected to Tableau via an OData feed for straightforward data transfer.

 

One of its key features of these connectors is that they can perform customized data exports.

You can also apply filters and select specific tables and fields (including custom ones you can create by working with data visualization consultants) to ensure only relevant data is transferred to Tableau.

You can also use these connectors for ongoing reporting: they support scheduled data refreshes on both Tableau Server and Tableau Cloud. So, they’re also very useful in helping you maintain up-to-date dashboards with the latest information.

 

12. Devart ODBC Tableau Connectors

Next up, we have another group of connectors by Devart ODBC.

This suite of Tableau Connectors is designed to help you connect Tableau to a wide array of databases and cloud services that lack native or partner-built connectors.

They function as a universal bridge: you can use them to access data from sources like Oracle, PostgreSQL, MySQL, Salesforce, Shopify, and QuickBooks directly within Tableau.

It does this by translating standard SQL queries into the native protocol of the target data source.

One thing I really like about these connectors is the high-performance Direct Mode. It establishes a native connection to the database or cloud service without requiring additional client software. This way, it both streamlines setup and improves data access speed.

It is important to note that using any ODBC connector, including Devart’s, requires additional configuration. So, you’ll need to install the specific driver on your machine and set up a Data Source Name (DSN) before you can connect through Tableau’s “Other Databases (ODBC)” option.

If you run into any difficulties, you might want to work with data visualization service providers – they can help you make the most of Devart’s Tableau connectors!

13. CData Tableau Connectors

CData Tableau Connectors are a suite of Tableau-certified third-party connectors.

They provide real-time SQL-based connectivity to over 250 data sources. You can use it to analyze live data in Tableau without running complex ETL processes.

These connectors are very useful for integrating data from applications, databases, and APIs with Tableau:

• SaaS applications like Salesforce, NetSuite, and SAP.
• Databases such as MongoDB and Cassandra.
• Cloud services like Google BigQuery and Amazon S3. 

One feature that stands out to me is that it supports both Live Mode and Data Extract Mode.

Live Mode provides instant access to real-time data for up-to-the-second insights, while Extract Mode allows for high-speed, in-memory performance and scheduled data refreshes.

The connectors expose rich metadata for automated data discovery, making complex data sources instantly Tableau-ready.

Lastly, you must note that CData offers these connectors through a subscription model, which provides access to the entire suite of over 200 connectors, along with product updates and dedicated technical support for the subscription duration.

14. Simba Tableau Connectors

Next up, we have the Simba Tableau Connectors – a suite of high-performance, enterprise-grade ODBC and JDBC drivers.

They help you connect Tableau with major big data and cloud data platforms.

Simba has built them to handle petabyte-scale data environments – so they’re perfectly suited to mission-critical dashboards where performance and consistent uptime are non-negotiable.

 

One of its most important features is pushdown processing: it optimizes query performance by pushing filters, joins, and aggregations directly to the data source. This allows it to reduce system load and speed up data retrieval in Tableau. They also offer SQL-based access to complex sources (Google BigQuery, Amazon Redshift, Hadoop, and Snowflake).

I also like that Simba has prioritized security as a central design principle of its Tableau connectors. So, its enterprise-grade features, including OAuth 2.0, Kerberos, and SSL/TLS encryption, meet strict compliance standards.

15. Progress DataDirect Tableau Connectors

The last Tableau connector on my list is Progress DataDirect’s suite of Tableau Connectors.

The suite includes a variety of third-party ODBC and JDBC drivers that provide standardized SQL access to a wide range of data sources.

What I really like about this suite is that you can use it to work with Tableau + other business intelligence tools.

Plus, they offer reliable connectivity to both on-premises and cloud-based data. So, whether you want to integrate relational databases, Big Data systems, NoSQL databases, or SaaS applications, Progress’ suite is the only one you’ll need to use.

A key feature is their ability to prepare these diverse and unstructured data sources for self-service analytics, allowing them to be visualized directly in Tableau. They are also certified against industry standards like ODBC and JDBC, ensuring compatibility and robust performance.

Lastly, Progress’s connectors come with robust security features. This includes protecting customer-sensitive data with encryption both at rest (AES-256) and in transit (SSL/TLS).

The connectors are designed for enterprise-scale use, with more than 10,000 global enterprises, including 96 of the Fortune 100, relying on them for their data connectivity needs.

Connect with Tableau and Start Visualizing Your Data

There you have it – a list of the 15 best Tableau connectors on the market.

All of them offer seamless and secure integrations with Tableau – but the main difference between them is twofold: what data they allow you to integrate with Tableau and their ease of use.

Some of the connectors I’ve mentioned, specifically the native tools, are available out-of-the-box but not versatile – they can only integrate specific databases.

Others, especially the third-party tools, are comparatively more difficult to install. But, they’re well worth the time and effort it takes to install because they can help you bring together multiple data sources.

However, if you’re not sure as to which Tableau connector you should use or need some help installing the connector of your choice, reach out to us at Augmented Tech Labs.

 

We specialize in helping SMBs, solopreneurs, and enterprises connect their business ecosystems with data visualization tools like Tableau.

So, tell us about your requirements, connect with us for a free consultation, and let us help you create a unified data visualization and analysis workflow for your operations!

Tableau Connectors: FAQs

1. What are Tableau data connectors?

Tableau data connectors are software bridges that link your data sources to Tableau, enabling direct data analysis and visualization without manual export processes.

 

2. When should I hire a data visualization consultant?

A data visualization consultant is ideal for complex connector setups, custom data modeling, and creating advanced, tailored dashboard solutions for your business.

 

3. What’s the difference between Tableau database connectors and cloud connectors?

Tableau database connectors link to on-premises systems like SQL Server, while Tableau cloud connectors integrate with SaaS platforms like Salesforce via web APIs.

 

4. What does the Tableau Salesforce connector do?

The native Tableau Salesforce connector pulls CRM data into Tableau for analysis, supporting data extracts and cross-database joins for a unified view.

 

5. Can third-party Tableau data connectors handle live data?

Yes, many third-party connectors support live data connections, allowing for real-time analysis of data from sources not natively supported by Tableau.

Choosing the wrong data visualization tool can lead to hours of wasted time mastering a platform and dollars going down the drain.

And your task of picking the right tool might become even more complicated when you’re comparing two heavyweights like Tableau and Domo.

But don’t worry: we’re here to help you make the decision easier through a comprehensive breakdown of the two tools.

Before we get started, you must remember that selecting the right tool isn’t just about features: it’s about picking the one that aligns best with your use case, existing tech stack and budget!

So, which one is the right engine for your data-driven journey:

Tableau, the undisputed market leader in data visualization, or Domo, the agile cloud contender, well-known for its all-in-one connectivity?

Dive in to find out!

Tableau vs. Domo: Table of Contents 

• TL;DR: Tableau vs Domo – Data Visualization Tools Compared Table
• What is Tableau?
• What is Domo?
• Tableau vs Domo: The Key Differences
• How to Choose between Tableau and Domo?
• Tableau vs Domo: Final Verdict
• Augmented: Helping You Choose Between Tableau vs. Domo
• Tableau vs Domo: FAQs

TL;DR: Tableau vs Domo – Data Visualization Tools Compared 

Looking for a quick comparison? I’ve got you covered: here’s a full breakdown of Tableau vs Domo based on all the key features of the two platforms:

What is Tableau? 

Tableau is the market leader in the data visualization tools market, with 14 out of every 100 users relying on it for their requirements.

It started as a Stanford project and has grown into the gold standard that many other data visualization services are measured against.

 

Source

Acquired by Salesforce, the Tableau dashboard software has one primary purpose: to help you see and understand your data through incredibly interactive and vibrant visualizations.

It combines ease of use with the technical features that data scientists and business analysts can use to visualize really complex data into powerful charts, maps, and graphs.

Standout Features of Tableau

• Unmatched Visual Flexibility:  This is where Tableau data visualization truly shines. For example, its “show me” panel and deep formatting options allow you to build highly custom, interactive dashboards that tell a compelling data story. The tableau dashboard software is thus perfect for analysts who need to explore every angle of a dataset.
• Advanced & Predictive Analytics: Tableau goes beyond basic charts. It has very good integrations with R, Python, and Salesforce Einstein. This means you can use it for predictive modeling, complex statistical analysis, and even demand forecasting. If you need to ask “why” something happened, Tableau’s got the tools you need to dig deeper.
• Flexible Deployment:  Unlike other purely cloud-based data visualization tools, Tableau offers a hybrid approach. You can start building on  Tableau Desktop  (a powerful Windows/Mac application) and then publish to Tableau Server (on-premise) or Tableau Online (cloud). This is a huge plus for organizations with strict data governance needs.

Also Read: How to Use Tableau?

Pros of Tableau

• A wide range of customizable visualization options.
• Powerful for ad-hoc analysis and deep dives.
• Huge, active community and a vast library of learning resources.
• Flexible deployment options.

Cons of Tableau

• The costs can mount quickly, especially as your user base grows.
• Once you’ve got the hang of it, Tableau can be pretty easy to use.
• You might need to use a separate tool like Tableau Prep for cleaning your data.

Who Should Use Tableau?

From what we’ve seen, Tableau can be a great option for: 

• Data analysts and scientists who need to perform deep, exploratory analysis.
• Large enterprises in finance, healthcare, or research that need on-premise solutions.
• Teams that need to create custom dashboards and printable reports. 

Tableau Pricing

Tableau has a transparent but layered per-user model:

• Viewer:  $15/user/month (offers “view” and dashboards interaction features).
• Explorer:  $42/user/month (for exploring trusted datasets).
• Creator:  $75/user/month (full capabilities, including Desktop and Prep).

What is Domo? 

Domo is a cloud-native business operating system that is more than just a normal data visualization software.

Through it, you can connect everyone in your organization, from the CEO to the front-line employee, via live data powered by a single, integrated platform.

Source

I often tell my clients to think of it as the smartphone of business intelligence: it can act as the one device that connects all your apps, messages, and information in a simple, accessible interface.

Let me show you how it works by exploring some of the best Domo features:

Standout Domo Features

• Massive Connector Ecosystem:  One of Domo’s core strengths is its vast array of  1,000+ pre-built connectors. Whether it’s Salesforce, Shopify, Snowflake, or a niche SaaS tool, Domo likely has a native connector to pull data in real-time. This makes it a versatile tool that can fit in with virtually any tech stack.
• AI & Automation (Mr. Roboto):  Domo has integrated AI into its core with features like NLP querying, which allows you to ask natural language questions (“Show me sales by region”), get automated insights, and even build predictive models with low code. Whatever the analytical process, there’s a chance that Domo will automate it for you.
• Collaboration & Apps (Domo Buzz & App Builder):  Domo functions like a social network for your data. For example, its Buzz feature lets users comment, tag, and alert each other directly on dashboards. Plus, you can use its low-code app builder to create custom data apps without writing a single line of code.

Pros of Domo

• Unbeatable number of easy, pre-built data connectors.
• Intuitive and collaborative interface for business users.
• Strong embedded analytics for customer-facing applications.
• Offers real-time data alerts and a pretty seamless mobile experience.

Cons of Domo

• Pricing is opaque and typically enterprise-level, often starting around $10,000.
• Less granular control over visualization design compared to Tableau.
• Doesn’t offer an on-premise option: it’s a cloud-only BI tool.

Who Should Use Domo?

Based on its features, pros, and cons, Domo might be a great option for:

• Mid-to-large-sized companies that use a vast array of SaaS applications and need them connected.
• Operational teams in marketing, sales, and retail that thrive on real-time, collaborative data.
• Organizations looking to embed analytics into their own products or customer portals.

In our experience, a combination of Domo features + a veteran data visualization services agency is the way you can create a completely automated, smooth, and secure data visualization infrastructure.

Domo Pricing

Domo uses a value-based, credit pricing model. The issue is that the pricing information is not publicly listed. So, you have to contact their sales team for a quote, but it’s known to be a significant enterprise investment, often competing with Tableau Creator-tier pricing at a minimum.

BI Tools Comparison: Tableau vs Domo

In this section, I’ll give you a feature-by-feature breakdown of the differences between Tableau and Power BI. Here’s how it stacks up:

1. Workflow: Dashboard Software vs. General BI Tool

The Tableau dashboard software gives you the best possible tools to build a masterpiece visualization from the ground up. You have total control to build customized charts and visuals (check out these Tableau dashboard samples) that you can easily share with your teams.

Domo, on the other hand, is like a general BI software. It provides the entire crew and pre-fabricated parts that you can use to create a data analysis and visualization workflow quickly and efficiently.

2. Ease of Use and Learning Curve

Tableau’s depth comes with complexity. So, if you want to run advanced calculations or create complex visualization, it has a steeper learning curve compared to Domo. Simply put, it’s built for power users, not those who want to take their first steps into the world of data visualization or analysis.

While Domo prioritizes user-friendliness, it does so on an enterprise level due to its pricing. That said, its drag-and-drop interface and app-centric approach allow non-technical users to build useful dashboards and get value faster.

3. Data Handling and Integration

While both connect to numerous sources, Domo’s 1000+ connectors are its primary advantage. It’s designed to be the central hub for all your cloud data with minimal effort.

Tableau, on the other hand, can connect to almost anything via its open + Java database connectivity. While it often requires more setup and data preparation work to blend these diverse sources effectively, it’s nothing you can’t take care of by working with a good data visualization services provider.

4. Collaboration and Governance

In this BI tools comparison, Domo is definitely the winner when it comes to collaboration. Its social features (Buzz) make discussing data as easy as commenting on a Facebook post. Plus, the governance is strong and cloud-centric, which means you can rest assured that Domo will do everything in its power to protect your data!

Tableau’s collaboration capabilities are more traditional (comments, subscriptions). Its approach to governance is useful for large, complex enterprises, especially since it offers on-premise deployment options.

How to Choose: Tableau or Domo? 

Still on the fence? Here’s how you can decide which of the two data visualization tools is best for you: 

Choose Tableau if:

• You need a tool for deep analysis and creating custom visualizations.
• You have data analysts or scientists on your team who will be the primary users.
• Flexibility (on-premise or hybrid cloud deployment) is a priority for security reasons.
• You value granular control over every pixel of your dashboard.

Choose Domo if:

• You need a tool for company-wide collaboration that sends real-time alerts to users.
• You want to connect countless cloud apps and databases quickly and easily.
• Your non-technical users might need to build apps and get insights without coding.
• You want an all-in-one platform that eliminates the hassle of using multiple tools.

Tableau vs. Domo: Final Verdict

So, which is better: Tableau or Domo?

As someone who’s worked in the data visualization services segment for more than 10 years, you’ll find my answer pretty boring: it depends on your use case!

I know it’s the most generic answer I can give you, but it’s also true!

For example, Tableau data visualization has no other rival in the market. But it’s pretty hard to use and get the most out of (unless you’re backed by a good data analyst, scientist, or consultant).

Similarly, no other BI tool comes close to Domo in terms of features and connectivity. But its pricing can make even enterprises think more than once before splashing the cash at it.

So, while there’s no one winner in general, there’s definitely one that suits your needs the best!

Augmented Systems: Helping You Choose Between Tableau vs. Domo, and Beyond

If you’ve read this far and are still wrestling with this decision, you’re not alone.

This is exactly the kind of strategic challenge we help our clients solve at Augmented Systems.

We don’t just help you visualize data: we empower you to build BI infrastructure that powers a data-driven culture.

When you work with us, you get:

• A complete audit of your requirements + tech stack to help you pick the right BI tool.
• Certified expertise in both platforms for implementation and dashboard development.
• End-to-end data visualization services to ensure you get maximum ROI from your BI ecosystem.

So, schedule a free consultation with our BI experts today, and we’ll help you navigate this choice to build the analytics powerhouse your business deserves!

Tableau vs Domo: FAQs 

1. Can Tableau connect to as many data sources as Domo?

Technically, Tableau can connect to anything via custom SQL or ODBC/JDBC. However, Domo wins on convenience with its 1000+ pre-built, managed connectors that require almost zero setup for popular cloud apps and databases.

2. Is Domo easier to learn than Tableau?

Generally, yes. Domo’s interface is designed for business users and is easier to pick up for basic dashboard building. Tableau has a steeper initial learning curve, especially for advanced calculations and custom visuals, but offers more power in the long run.

3. Which tool is better for large enterprises: Tableau vs Domo?

Both are enterprise-grade data visualization tools.  While Tableau might be more suitable for traditional, large enterprises that have complex data governance and on-premise requirements, Domo is a strong contender for agile, cloud-first companies that value company-wide adoption and connectivity over deep, granular analysis.

4. How does pricing really compare between Tableau and Domo?

Tableau has a clear, public per-user price tag, which can become expensive at scale (especially with a mix of Creators and Viewers).  Domo’s pricing is custom and typically starts at a high enterprise level, often making it less accessible for small to mid-sized businesses without significant budgets.

5. Which tool has better mobile support?

Both have excellent mobile apps.  Domo is often praised for its mobile-first design and superior experience for viewing and interacting with data on the go, making it a favorite for executives and field employees.

If you’re still using raw data analysis with a bunch of numbers and figures, you’re losing both time and money!

For example, data visualization enables enterprises to make decisions nearly 70% faster compared to just traditional, raw data analysis.

In specific segments, like e-Commerce and logistics, charts and graphs help enterprises boost conversion rates and even minimize their operational downtime.

In short, data visualization is the key to making faster and smarter decisions based on information you already have.

In this blog, we’re going to discuss the vital and growing importance of data visualization and share with you the best techniques + tools for data visualization.

We’ll also tell you how expert data visualization services can help you leverage real-time dashboards in your decision-making processes while relieving you of burdens like technical integration.

Let’s dive in!

What is Data Visualization: Table of Contents

• What is Data Visualization: Going Beyond Numbers
• 5 Key Benefits of Data Visualization
• Techniques and Types of Data Visualization
• Best Data Visualization Tools
• Why Work with a Data Visualization Consultant
• Augmented Tech Labs: Your Ideal Data Visualization Services Partner
• What is Data Visualization: FAQs

What is Data Visualization: Going Beyond Numbers

Data visualization is the art and science that transforms raw data into visual contexts that simplify and contextualize patterns, trends, and correlations for decision-making.

Here’s how it works: you use charts, graphs, and maps to visualize a picture that is painted by your data. This translation of abstract numbers into vibrant visuals can help you, as a decision-maker, cut through the clutter and clearly identify the overall health of your business.

Over the years, data visualization has gone from being a luxury or a creative way of interpreting data to a critical business competency. Simply put, if data analysis can make a difference to your decision-making process, data visualization can accelerate and enhance the quality of those decisions!

Core Concepts in Data Visualization

The data visualization process rests largely on four very important concepts:

• Visual Encoding: This is the process of mapping data onto visual variables, such as position, size, shape, and color.
• Dashboarding: Dashboarding is the process of combining multiple visualizations into a single interface for monitoring key metrics. This is particularly important for executives who need to keep track of a lot of metrics without moving between different pages, websites, or charts.
• Interactivity: Interactivity means allowing users to manipulate visualizations to explore different aspects of the data. You can use it to visualize predictive models, test different solutions, and extract contextual information by controlling the variables of your visualizations.
• Storytelling: Perhaps the most important part of visualization, it involves using charts and graphs to guide viewers through a narrative about what the data reveals.

Also Read: The Best Data Visualization Techniques in 2025.

 

5 Key Benefits of Data Visualization

There are five key benefits of data visualization that we’ve observed over the time that we’ve worked with a wide range of clients:

1. Faster Decision-Making

Human brains are hardwired to interpret visual information faster than a bunch of words or numbers. That’s why data visualization is key to driving faster decisions.

Think of data visualization as creating a series of insightful snapshots into your business processes. It’ll give you the edge of cognitive efficiency and even save you time! For example, employees are 28% more likely to find the information they’re looking for through visualized data.

2. Identifying Trends and Patterns

Complex correlations that our brains might take hours and hours to understand, data visualization identifies within minutes, even seconds!

For example, a heat map can instantly reveal geographic patterns in customer behavior that would require sophisticated regression models (and more time!) to detect with raw data.

3. Improved Collaboration

When you’re working with sales teams that don’t understand revenue KPIs and marketing teams that find it difficult to understand sales numbers, you need a common language that can make collaboration easier.

That’s exactly what data visualization services bring to the table: they help you create concise dashboards that all teams can easily understand. In fact, research we’ve come across shows that orgs that rely on data visualization techniques experience 40% better cross-departmental alignment on strategic initiatives!

4. Data-Driven Stories

Data analysis gives you insights but data visualization can help you tell convincing stories. That’s because visuals empower you to engage emotionally and intellectually with your stakeholders: they help you make information accessible to everyone who needs to understand it.

For example, presentations that rely on visuals are 47% more persuasive than those that rely only on verbal arguments.

5. Real-Time Insights

The ultimate goal of collecting and analyzing data is not just to understand what happened in the past. It’s to predict what will happen in the future and take preventive actions in real-time.

That’s exactly what data visualization tools help you achieve: rather than waiting on periodic reports to filter through departments, you can get quick access to real-time movements in your enterprise’s most vital performance indicators.

Techniques and Types of Data Visualization

There are a lot of different types of data visualization techniques you can use depending on the outcome you want to achieve or the metric you want to monitor.

Here’s a table that outlines the most popular visualization techniques, their best use-cases, examples, and tools:

For a more detailed breakdown into when, why, and how to use these methods, check out our guide on the best data visualization techniques.

 

Best Data Visualization Tools

When it comes to which tools are the best, each data visualization consultant has their own preference. However, we’ve drawn up a list of four tools that you can explore right away to get started with your data visualization journey:

• Microsoft Excel: Despite being a traditional tool, Excel is a great option for creating basic charts and graphs. In fact, with the recent versions adding more advanced visualization capabilities, it remains one of the best basic tools on the market.
• Google Sheets: As part of the Google Workspace ecosystem, Sheets provides collaborative chart creation with easy sharing options. It’s also simple and gives you a glimpse of the difference a cloud-based visualization tool can make to your decision-making process! You might particularly like how it shows a preview of the different data visualization examples based on your dataset. 
• Power BI: Power BI is Microsoft’s native business intelligence platform. It excels at transforming data from various sources into cohesive and interactive reports. If you’re looking for a tool that can help you with robust data modelling, real-time dashboard capabilities, and enterprise-level reporting, Power BI might be a good option.
• Tableau: The undisputed market leader in business intelligence visualization, Tableau helps you create a wide range of interactive charts and dashboards that can be shared online. We’ve had great success in using Tableau to help our clients create executive dashboards that they rely on to make critical decisions.
• Domo: An enterprise-grade tool, Domo is one of the best options if you want to embed visualization capabilities into websites, apps, and even internal software systems. It’s the best option for enterprises that want a BI platform that their non-technical staff can use to collaborate with each other.

Also Read: Top Data Visualization Tools in the Market in 2025

Why Work with a Data Visualization Consultant?

As of 2025, the global data visualization services market is a multi-billion-dollar industry. And there are very good reasons why this is the case.

For example, the past few years have witnessed the:

• Rise of AI-powered storytelling.
• Increasing complexity of data visualization tools.
• Development of real-time data streams.

Now, it’s quite natural that you might not want to invest too heavily in keeping up with all these different trends by hiring or constantly upskilling your personnel.

Even if you have the time and the budget to do so, working with data visualization consultants can help you cut costs and give you a reliable partner whose entire job is to power your ability to make decisions through interactive dashboards that highlight actionable insights.

They possess core competencies like industry experience, technical expertise, design capabilities, and an analytical approach that they can tailor to your requirements.

That’s why more and more enterprises are relying on data visualization services to give them the tools they need to make smarter and quicker decisions.

Augmented Systems: Your Ideal Data Visualization Services Partner

In the contemporary business environment, actionable data visualization can be the difference between you making the right decision at the right time vs. missing out on critical growth opportunities you need to leverage.

To leverage the power of visualized data, all you need is the right combination of tools + techniques + partner that can help you create customized dashboards and visualizations.

That’s where we at Augmented Systems come in – we have decades of experience adapting to every single trend in data visualization, and ensuring that our clients make the most out of the data they collect.

We offer end-to-end data visualization consulting services, including:

• Custom dashboard development tailored to specific business needs.
• Data migration, standardization, cleaning and preparation.
• Staff training and enablement for self-service visualizations.
• Ongoing optimization and refinement based on user feedback.

So, whether you need help choosing the right tool, maintaining a data visualization ecosystem, or custom dashboard engineering capabilities, we’ve got you covered! Let us build visualizations that align closely with your requirements, so that you can keep doing what you do best: running your business like a smooth operation!

Reach out to us for a free consultation, tell us about your priorities/problems/goals, and we’ll get back to you with a comprehensive data visualization strategy!

What is Data Visualization: FAQs

1. What are the most common types of data visualization?

Common types of data visualization techniques include charts (bar, line), geospatial maps, hierarchical charts (treemaps), and interactive dashboards. The “best” type depends on the story your data needs to tell and your specific goal.

2. Why should I hire a data visualization consultant instead of doing it in-house?

A data visualization consultant brings expert knowledge of the latest tools and techniques. This saves you time and cost while ensuring you get professional, actionable dashboards tailored to your business needs.

3. What are some real-world data visualization examples?

Some of the best real-world data visualization examples that we’ve come across include:

• An e-commerce conversion funnel dashboard for a CMO to track customer journey drop-offs. 
• A logistics operations centre uses a live map to monitor fleet locations and delivery times.
• A CFO’s financial KPI dashboard visualizes cash flow, revenue vs. targets, and departmental spend in real-time.

4. What should I look for in data visualization services?

We recommend looking for a service that offers end-to-end support: custom dashboard development, data cleaning, and team training. The right partner will provide techniques and tools that fit your specific industry and goals.

5. How do I choose the right data visualization tools for my business?

To choose the right data visualization tool for your business, consider your team’s skill level and your project’s complexity. Your options range from simple tools like Google Sheets for basics to powerful platforms like Tableau for advanced, interactive business intelligence dashboards.

Tableau is one of the most popular business intelligence and data visualization tools on the market. But it asks you to pay between $70 (for individual users) and $165,000 (for enterprise licenses)!

And even if you’re willing to break the bank for Tableau, you still get hit with:

• A steep learning curve for complex operations.
• No native scheduling capabilities.
• Minimal data cleaning and processing options.

Plus, if you need to visualize or process million+ rows, you may experience performance issues, especially if you’re using a live connection!

Thankfully, there are several great Tableau alternatives on the market that offer better data visualization and BI functionality at more affordable prices.

In this blog, I’m going to walk you through 11 such Tableau competitors. We’ll cover everything from the best open source tools to the ones recommended especially by data visualization consultants.

Let’s dive in!

Tableau Alternatives: Table of Contents

• TL;DR: Which Tableau Alternative is the Best?
• Tableau Alternatives: Table of Comparison
• 11 Best Tableau Alternatives for 2025
• Which Tableau Alternative is Right for You?
• Tableau Alternatives: FAQs

TL;DR: Which Tableau Alternative is the Best?

While different Tableau alternatives have their own strengths and limitations, I’ve described all 11 Tableau alternatives that work for different use cases. Find out which one aligns with your requirements:

• Best Enterprise-Grade Alternative: MicroStrategy (Strategy), which offers row-level security, AI-driven insights, and Bitcoin treasury integration for large-scale deployments.
• Best Free Alternative: Helical Insight, an open-source tool with pixel-perfect reporting and workflow automation, ideal for budget-conscious teams.
• Best for Embedding: Sisense, powered by ElastiCube engine and SDKs, which enable seamless white-label dashboards in apps.
• Best AI-Powered Alternative: ThoughtSpot, backed by Natural language search (SpotIQ) and autonomous AI analytics for non-technical users.
• Best for Microsoft Ecosystems: Power BI, which costs just $10/user/month, and comes with deep Excel/Azure integration + Copilot AI.
• Best for Ad-Hoc Exploration: Qlik Sense with its associative engine that uncovers hidden data relationships without predefined queries.
• Best for Real-Time Analytics: Domo, with 5-minute auto-refresh cycles and 1,000+ connectors for live dashboards.
• Best for SQL-Centric Teams: Looker, backed by LookML semantic layer, which ensures metric consistency across Google Cloud workflows.
• Best for Developers: Apache Superset, a free, SQL-first, and customizable Tableau alternative with 40+ visualization types.
• Best for SMBs: Zoho Analytics, which costs $24/month, and comes with an AI assistant “Ask Zia,” along with 500+ integrations.
• Best Lightweight Alternative: Metabase, a self-hosted or cloud Tableau alternative, with no-code queries, and a simple, 5-minute setup.

Tableau Alternatives: Table of Comparison

In a hurry? I’ve got you covered!

Check out this table of comparison of the 3 best Tableau alternatives on the market.

 

1 1 Best Tableau Alternatives for 2025

Here’s my list of the best Tableau alternatives, including the top data visualization tools and business intelligence tools on the market:

1. Microsoft Power BI

Best For: SMBs that need a scalable platform and are already using other Microsoft products.

First on my list is Microsoft’s native data visualization platform – Power BI. It also doubles up as a data visualization tool like Tableau.

It offers a wide range of features such as interactive dashboards, AI-driven insights, and integration with several data sources.

Standout Features of Power BI

• Real-Time Dashboards: Power BI’s dashboards can help you live-stream data from 500+ sources. The dashboards also auto-refresh to give you the latest data. 
• Excel Integration: You can directly import and export data between Microsoft Power BI and Excel through the PivotTable functionality. 
• AI Analytics: Microsoft has integrated Copilot with Power BI, which means you can use it to raise text-based queries and get data insights in return!

Also Read: How to Use Power BI Like a Pro?

Pros of Power BI

• Affordable pricing plans.
• Very smooth integration with other Microsoft products.
• Good mobile support through a dedicated app.

Cons of Power BI

• Steep learning curve for complex queries.
• Limited customization for visuals. 

Power BI Pricing

• Pro: $14/user/month
• Premium: $24/user/month
• Fabric: Custom pricing for enterprise needs.

2. Qlik Sense

Best For: Teams in data-heavy industries that need ad-hoc explorations without predefined queries.

Qlik Sense is an AI-powered, enterprise-grade Tableau alternative.

What makes it special is its unique associative engine that empowers dynamic data collaboration, real-time insights, and predictive analytics.

Let me show you why it can be an excellent alternative to Tableau.

Why Qlik Sense is a Good Power BI Alternative

• Associative Engine: Qlik Sense doesn’t restrict you to predefined queries or hierarchies, so you can create and define relationships between data points based on your requirements.
• AI Analytics: Qlik’s native Insight Advisor provides you with context-aware analytics, which is more advanced than Tableau’s Ask Data, which lacks context-awareness.
• Real-Time Action: You can get automated alerts in real-time directly to your preferred workflow apps like Slack. 

Pros of Qlik Sense

• Very quick performance with an in-memory engine.
• Offers very good embedding and white-label capabilities.
• Particularly useful for AI or ML applications.

Cons of Qlik Sense

• Might be expensive for small teams or startups.
• Very steep learning curve for non-technical users.
• Some features (like predictive analytics) are only available with the most expensive plan.

Also Read: Tableau vs. Qlik Sense: Which One Should You Choose for Data Visualization?

Qlik Sense Pricing Plans

• Starter: $200/month.
• Standard: $825/month.
• Premium: $2,750/month.

3. Looker (Google Cloud)

Best For: Teams that rely heavily on SQL databases and querying systems or Google Cloud users who are already using BigQuery.

Looker is a modeling-centric business intelligence tool like Tableau.

It is powered by LookML, an SQL-based semantic layer. It was acquired by Google and now integrates well with all other Google products, including Cloud and BigQuery.

It can be a great Tableau alternative if you’re looking for advanced governed analytics and embedded dashboard capabilities.

Why Looker is a Good Power BI Alternative

• Semantic Layer: LookML enforces strict data standardization, ensuring that you get consistent metrics across all reports. 
• Real-Time BigQuery Integration: Looker runs queries directly from BigQuery in real time. More importantly, it can do so without any time-consuming extractions, unlike Tableau. 
• Embedded Analytics: Looker’s API-first architecture is perfect for seamless white-labeling and agency requirements. It far outperforms Tableau’s clunkier, more expensive API capabilities.

Pros of Looker

• Strong row-level security.
• Single source of truth, unlike Tableau’s decentralized approach.
• Deep Google Cloud integration. 

Cons of Looker

• Pricing might be too expensive for SMBs and startups.
• Minima support for mobile functionality.
• Limited visualization options.

Looker Pricing Plans

Looker can cost you anywhere between $35,000 and $150,000+ annually, depending on your requirements.

4. Domo

Best For: Mid-sized enterprises that need real-time data monitoring.

Domo makes my list of the best Tableau alternatives as a cloud-native BI platform.

It combines real-time dashboard with AI analytics and expansive integration capabilities with a mobile-first design and ETL tools.

Why Domo is a Good Power BI Alternative

• Real-Time Data Processing: Domo’s dashboards are designed to automatically refresh every five minutes, outperforming Tableau’s manual or scheduled refreshes.
• Built-in Collaboration Capabilities: With features like Domo Buzz and annotations, your team can discuss data directly on dashboards without switching to another tool.
• Magic ETL: You need any SQL knowledge to use Domo’s ETL functions, which is not the case with Tableau. 

Pros of Domo

• Supports 1,000+ data connectors.
• Offers a mobile app with offline access.
• HIPAA and SOC 2 compliant tool.

Cons of Domo

• Domo can slow down when handling large datasets.
• Very costly, even when compared to Tableau’s high pricing.
• Limited advanced visuals.

Domo Pricing Plans

Domo’s pricing plans start at ~$15/user/month and can go up to a minimum $10K/year for small teams.

While its enterprise plans exceed $150K/year, you can also opt for a credit-based model for data volume.

5. Sisense

Best For: Developers that need to embed BI and data visualization features into their SaaS products.

Sisense is an AI-powered, embed-friendly Tableau alternative.

Unlike other data visualization tools, Sisense specializes in data modeling for seamless integration into other applications.

Let me show you why it’s hugely popular with developers around the world:

Why Sisense is a Good Power BI Alternative

• In-Chip Engine: Sisense gives you access to its proprietary ElastiCube technology, which can easily process real-time queries for datasets with billion+ rows.
• SDK-Driven Embedding: Sisense is an embed-first platform and works very well with apps and websites powered by Angular, React, and Vue frameworks. 
• Advanced AI automation: While Sisense comes with automated anomaly detection insights, Tableau requires manual setup for advanced AI features.

Pros of Sisense

• Extremely fast queries with ElastiCube.
• SOC 2 and ISO 27001 compliant tool.
• Supports 400+ data connectors. 

Cons of Sisense

• Requires knowledge of Compose SDK functionality. 
• Not very scalable as the costs mount quickly with multi-tenant setups. 

Sisense Pricing Plans

Sense is extremely expensive, with plans starting at ~$40,600/year (Essential tier, 5–15 users).

Its Enterprise plans are even more expensive, exceeding $327,000/year (unlimited ElastiCubes, AI features).

You might also encounter hidden costs like viewer licenses, data connectors, and professional services add 20–30% to base fees.

6. Zoho Analytics

Best For: SMBs that need a cost-effective business intelligence solution.

Zoho Analytics is an AI-powered, self-serve BI tool that integrates with 500+ data connectors and features drag-and-drop visualization capabilities.

It could be your go-to Tableau alternative if you need a user-friendly tool that can be used by non-technical teams.

Why Zoho Analytics is a Good Power BI Alternative

• Built-in Data Prep: Zoho automatically cleans and processes your data, whereas Tableau requires you to purchase the data cleaning service separately.
• AI Features: Zoho’s “Ask Zia” can generate reports in response to simple text-based queries. It can even diagnose anomalies and suggest corrective actions. 
• Embedded Analytics: Zoho’s embedding and white-label capabilities are more seamless as well as more affordable compared to Tableau’s.

Pros of Zoho Analytics

• Zoho is 50% cheaper compared to Tableau.
• Comes with pre-built templates for 25+ business apps.
• Features 500+ connectors.

Zoho Analytics of Looker

• Slow performance for datasets with 50M+ rows.
• Comes with fewer advanced visualization capabilities.

Zoho Analytics Pricing Plans

Zoho Analytics is free to use for 2 users and up to 10K rows.

Its paid plans start at $24/month and go up to $575/month for enterprise use-cases.

7. ThoughtSpot

Best For: Non-technical teams that need a Google-like search for their data.

ThoughtSpot is one of the best data visualization tools on the market.

While data visualization consultants use them for enterprise-grade BI requirements, I’ve also seen SaaS developers leverage them for in-app embeds.

It thus makes my list of Tableau competitors as one of the most versatile BI platforms with a wide range of applications.

Why ThoughtSpot is a Good Power BI Alternative

• NLP Queries: ThoughtSpot features a special tool called SpotIQ, which can generate data-backed answers to text-based queries like, “Why did sales drop in March?”
• Live Data Exploration: You can get faster, real-time responses from ThoughtSpot compared to Tableau, as the former runs directly on cloud data warehouses like BigQuery.
• Embedded Analytics: Comes with SDKs and API integration that supports seamless embedding for both agency white-labeling and mobile/web applications.

Pros of ThoughtSpot

• Doesn’t need you to have any SQL knowledge.
• Strong row-level security.
• SOC 2 and HIPAA compliant tool.

Cons of ThoughtSpot

• Limited visualization options.
• Expensive embedding pricing ($5/dashboard).
• Complex setup for data modeling.

ThoughtSpot Pricing Plans

ThoughtSpot offers different plans for analytics and embedding.

Analytics plans start at $50/user/month for 5M rows and 5 users.

Embedded Plans come with consumption-based pricing ($$$/query). I’ve also heard that ThoughtSpot’s costs are unpredictable for heavy usage.

8. Apache Superset

Best For: Startups and SMBs that need an open-source, scalable BI platform.

Apache Superset is the only open-source Tableau alternative on my list.

It’s not just free, it’s also extremely lightweight, making it a top choice among developers and data visualization consultants that are familiar with SQL.

Why Apache Superset is a Good Power BI Alternative

• Flexibility: Superset is 100% free and still allows unlimited customization, including custom visualizations plugins with JavaScript.
• SQL Workflow: Superset’s SQL Lab IDE enables complex joins, templating, and query optimization, making it ideal for data engineers. 
• Scalable: You can easily scale your BI functionality with Superset’s cloud-native architecture that requires zero data ingestion.

Pros of Apache Superset

• Zero licensing costs. 
• 40+ data visualization options.
• Direct querying without any extracts. 

Cons of Apache Superset

• Steep setup that requires technical knowledge. 
• Very weak mobile experience. 

Apache Superset Pricing Plans

While Apache Superset is completely free if self-hosted, you can also opt for its managed hosting service, which is free for up to 5 users and then costs $20/user/month.

9. MicroStrategy

Best For: Enterprises that require centralized data governance and compliance.

Strategy, formerly called MicroStrategy is an AI + BI platform that brings together advanced analytics, AI-driven insights, and Bitcoin treasury management.

It makes my list of Tableau alternatives as an enterprise-grade BI tool with limited but robust data visualization capabilities.

Why MicroStrategy is a Good Power BI Alternative

• Semantic Graphs: MicroStrategy’s Semantic Graphs enforces strict business rules that you can define to deliver consistent results across reports.
• HyperIntelligence: It delivers contextual insights directly to apps like Outlook or CRMs like Salesforce.
• Enterprise-Grade Scalability: Works seamlessly with pentabyte-scale datasets with in-memory support and multi-tenancy support. 

Pros of MicroStrategy

• Completely centralized governance for your data. 
• Offers predictive analytics and support for text-based queries. 
• Enterprise grade security with SOC 2 and HIPAA compliance.

Cons of MicroStrategy

• Very high costs, even compared to Tableau’s expensive pricing.
• Less visualization options compared to Tableau.
• Steep learning curve. 

MicroStrategy Pricing Plans

While MicroStrategy only offers custom pricing, the data visualization consultants I’ve worked with report that the Starter plan costs ~$35,000/year (small teams) and Enterprise plans cost up to $150,000+/year (unlimited users, AI features).

Also Read: Tableau vs MicroStrategy – Which Data Visualization Tool is Better?

10. Metabase

Best For: Non-technical teams and users who need a BI tool with a drag-and-drop interface.

Metabase is another open-source, lightweight Tableau alternative.

It’s designed primarily for self-service analytics and comes with decent no-code querying and interactive dashboards.

Why Metabase is a Good Power BI Alternative

• No-Code Architecture: Regardless of how complex your query is, you don’t need any SQL knowledge to build queries in Metabase.
• Cost Efficient: While Metabase is completely free to use for low-level capabilities, even its pro plan costs just $85 compared to Tableau’s $850.
• Embed Analytics: Metabase’s pro plan comes with smooth white-labeling capabilities and interactive embedding via API or SDKs.

Pros of Metabase

• Easy setup and can be deployed in minutes.
• Backed by strong community support.
• Sends alerts directly to apps like Slack.

Cons of Metabase

• Slows down when working with datasets containing 50M+ rows.
• Limited advanced visualization options. 

Metabase Pricing Plans

• Open Source: Free (self-hosted).
• Starter: $85/month (5 users + $5/user extra).
• Pro: $500/month (10 users + $10/user extra).
• Enterprise: Custom (starts at ~$15K/year).

11. Helical Insight

Best For: Enterprises that need to create highly compliant reports or developers that need API customization.

Last on my list of Tableau alternatives is Helical Insight.

It’s an open-source but enterprise-grade BI platform that offers pixel-perfect reporting, embedded analytics, and workflow automation.

Why Helical Insight is a Good Power BI Alternative

• Canned Reporting: Generates document-style reports that you can print, making Helical especially suited to enterprises that need to generate compliance reports.
• Workflow Automation: Helical Insight automates report bursting, scheduling, and alerts; Tableau only offers this feature through third-party integrations. 
• Flat Pricing: Helical Insight’s Community Version is free to use, while even the paid versions don’t charge you per user.

Pros of Helical Insight

• White-label embedding supports full rebranding.
• Offers unified metrics even across databases.
• Provides direct support for developers.

Cons of Helical Insight

• The setup is complex and requires DevOps or IT support.
• Supports fewer native visualization options compared to Tableau.

Helical Insight Pricing Plans

• Community Edition: Free (self-hosted).
• Enterprise: Custom flat pricing (~$35K/year for core features)

Which Tableau Alternative is Right for You?

In this blog, I’ve walked you through the 11 best Tableau alternatives and competitors on the market.

So, which one is right for your business intelligence and data visualization requirements?

As a veteran data visualization consultant, my answer is that the best tool depends on your use case and budget, and whether you want a tech-savvy or user-friendly solution.

For tech-savvy users, I recommend going with Domo or MicroStrategy. They’re also good for enterprise use cases.

For users that want good visualization options with user-friendly interfaces, I suggest giving Looker, PowerBI and Zoho a shot. They’re relatively easy to use and come with decent support.

And if you want to find out which of the best data visualization tools we’ve discussed above suit your use-case with extreme precision, why not connect with us?

At Augmented Systems, we specialize in helping growing startups, thriving SMEs, and established enterprises find the best solutions for their data visualization needs.

Reach out to us, tell us about your requirements, and let us do the heavy lifting so you can focus on the thing that matters: making smarter decisions with data-backed insights.

Tableau Alternatives: FAQs

1. Which Tableau alternative is best for small businesses?

Zoho Analytics ($24/month) or Power BI ($10/user/month) are ideal for SMBs. Both offer affordability, ease of use, and solid integrations—Zoho for AI automation, and Power BI for Microsoft ecosystem users.

2. What’s the best free alternative to Tableau?

Helical Insight (open-source) or Apache Superset (free, SQL-friendly). Helical excels in compliance-ready reports, while Superset is perfect for developers needing customization.

3. Which tool beats Tableau in real-time analytics?

Domo wins with 5-minute refreshes and 1,000+ connectors. Perfect for live dashboards, though it’s pricier than Tableau.

4. Is there a Tableau alternative with better AI features?

ThoughtSpot (NLP search) and Power BI (Copilot AI) lead here. ThoughtSpot answers plain-English questions; Power BI integrates AI seamlessly with Excel/Azure.

5. Which alternative is best for embedding analytics?

Sisense (ElastiCube engine) or Looker (LookML APIs). Sisense offers SDKs for devs; Looker ensures metric consistency in embedded dashboards.

“Is there any way to make Excel analysis go faster?”

That’s a question I’ve heard too many times as a data visualization consultant.

The good news is that it’s a problem you can solve easily by combining the strengths of Excel with the capabilities of Power BI, Microsoft’s native data analysis tool.

Whether you’re an analyst who needs to analyze datasets with million+ rows, a fintech executive who needs real-time analysis, or an IT manager concerned about Excel’s lack of security, the Excel Power BI integration is what you need!

In this blog, I’m going to show you how you can leverage Power BI Excel connectors to analyze huge datasets and securely share insights with team members.

Here’s what I’ll cover:

 

• 3 proven methods to connect Power BI with Excel (including free options).
• When to use each tool: avoid “Excel hell” and “Power BI overkill.”
• Best practices that I stand by as a data visualization consultant.

Let’s dive in!

How to Use Power BI with Excel: Table of Contents

• What is Power BI?
• Advantages of Using Power BI with Excel
• How to Connect Power BI with Excel?
• How to Use Power BI with Excel?
• How to Use Power BI with Excel: Best Practices
• You’re Ready to Maximize the Combination of Power BI with Excel
• How to Use Power BI with Excel: FAQs

What is Power BI?

Power BI is Microsoft’s native business intelligence and data visualization tool.

Its core strength and function is to take raw data from different sources and convert it into user-friendly reports. You can use it to break down data into stories, discover hot trends behind cold numbers, and make smarter, data-driven decisions.

Let me briefly show you the features that Power BI offers.

Features of Power BI

• Connects with multiple data sources, including Microsoft Excel.
• Optimized to work with millions of rows of data.
• Lets you clean, model, and analyze data using Power Query and DAX queries.
• Offers multiple data visualization options, including charts, graphs, and maps. 
• Power BI Service helps you securely share insights with your team.

As you can see, Power BI offers a lot of enterprise-grade features that can empower you to get actionable insights from large data sets. Thus, Power BI compensates for one of Excel’s main limitations.

Also Read: Top 9 Features of Power BI You Need to Know in 2025

Advantages of Using Power BI with Excel

There are 7 main advantages that you can gain by using Excel Power BI dashboards. These include:

1. Familiarity and Flexibility with Data Modeling

A majority of the analysts and executives start their journey into the world of data with Excel.

In fact, even with the rise of other databases and dataset viewers, Excel remains the universal favorite when it comes to running quick calculations, financial modeling, and ad-hoc analysis.

But using Excel alone might be limiting as its performance lags with large datasets.

 

Whereas, when you combine its powerful capabilities with the ease & scalability of Power BI, you can get more benefits than just using Excel and flexibility to switch between the two platforms.

In fact, I’ve seen many data visualization consultants switch between the two platforms depending on their requirements!

2. Granular Data Manipulation

Another benefit of using Excel is that you can manually edit individual cells, apply custom formulas, and tweak them whenever you want.

Simply put, it’s great for small and medium databases of less than 1 million rows.

So, you can use it to analyze specific datasets with limited rows or data points, and switch to Power BI for analyizing larger datasets.

3. Offline Accessibility

One of the best parts about Excel is that you only need computing power to use it.

This means you can access your data regardless of whether you’re connected to the internet.

Its offline accessibility thus makes Excel an invaluable tool in your arsenal!

4. Handles Massive Datasets

If you’ve Excel sheets with millions and billions of rows without the computing power or Excel features to process them, Power BI is the tool you need.

It’ll integrate perfectly with Excel and eliminate performance lags with optimized compression and powerful cloud computing.

5. Interactive, Dynamic Visualizations

While Excel offers 25+ data visualization types, Power BI offers nearly double this number, with 45+ options. This includes Sankey diagrams, AI-powered charts, and more.

Plus, Power BI gives you features like Drill Down, Cross-Filtering, and Tooltips you can use to gain deeper insights into your data.

Pro Tip: Data visualization services like Augmented’s can help you leverage the complete capabilities of powerful tools like Power BI while eliminating the time required to master its features. 

6. Real-Time Collaboration

If you’re working with sensitive financial, healthcare, or customer data and need a data visualization tool that also guarantees safety, you can benefit from using both Power BI and Excel.

You can collect, store, and organize data in Excel sheets while sharing insights and analysis directly through Power BI Service.

It’ll eliminate the need to email sensitive data to users within or outside your organization, while Power BI Excel connectors will ensure that your insights stay fresh.

7. Advanced AI and Natural Language Querying

Lastly, if your team consists of both technical and non-technical users, you should definitely consider using both Excel and Power BI to get the best of both worlds.

That’s because Power BI comes with advanced AI that lets you create reports through simple, text-based queries.

So, you can just ask it to “Create a Report on the Sales in the North American region for Q1 of this year,” and it’ll automatically generate the report for you!

Also Read: Power BI vs. Excel: Which is Better for Data Visualization?

Power BI & Excel Connectors: How to Integrate Them Together?

There are three ways you can connect Power BI with Excel. Let me quickly walk you through all three of them:

Method 1: Import Excel Data into Power BI

Under this method, you’re basically uploading Excel data to Power BI to analyze it visually. Here’s the process you need to follow:

• Open Power BI Desktop → Select “Get Data” → Choose Excel.
• Browse and select your Excel file.
• Use Power Query Editor to clean and transform data (you can change data types, filter rows & more).
• Click “Close & Apply” to load data into Power BI.

Method 2: Analyze Power BI Data in Excel (Analyze in Excel Feature)

Under the second method, you’re doing the opposite: using Power BI to create an Excel sheet where you can analyze the data.

Follow this three-step-process for to create your Excel file:

• In Power BI Service, open a report → Click “Analyze in Excel”.
• The system generates an Excel file with a live connection to the Power BI dataset.
• Use PivotTables, charts, and Excel formulas to analyze the data.
  

Note: You’ll need a Premium or Pro subscription to both create and view the report to use this method.

Method 3: Export Power BI Data to Excel

You can also manually export data through a refreshable Excel table. Here’s what you need to do:

• In a Power BI report, click “Export Data” (…) on a visual.
• Choose “Summarized Data (.xlsx)” for a refreshable Excel table.
• Open the file in Excel → “Enable Editing” to interact with live data.
  

How to Use Power BI with Excel?

Now, we get to the main question: how can you use Power BI with Excel to leverage the best features of both tools? Let’s find out:

1. Create Power BI Reports from Excel Data

The first way to use Power BI with Excel is to prepare your data in an Excel sheet and upload it to Power BI for analysis.

Here’s how you can do it:

Process

Step One: Prepare Excel Data

Format as a Table (Ctrl+T) and clean data (remove blanks, standardize formats)

Step Two: Import into Power BI Desktop

Go to “Get Data” → Excel → Select file → Transform in Power Query if needed.

Step Three: Build Visualizations

Drag-and-drop fields to create charts, tables, or maps.

Step Four: Publish to Power BI Service (Optional)

Share dashboards with teams via the cloud.

Who Should Use This Method?

This method is ideal for:

• Excel power users transitioning to BI tools.
• Small businesses which need basic dashboards without complex setups.

Ideal Use Case

• Turning monthly sales reports (Excel) into interactive Power BI dashboards.

Will You Need a License to Use This Method?

No, since Power BI Desktop is free (but doesn’t offer sharing capabilities), you won’t need a license to integrate Power BI and Excel by using this method.

However, you’ll need a Pro/Premium required to publish reports to Power BI Service.

2. Use “Analyze in Excel” to Explore Power BI Datasets

The second method, using the “Analyze in Excel” feature to explore Power BI datasets, is very useful for anyone who is used to Excel but needs to process large amounts of data.

Here’s the process you need to follow:

• Step 1: Go to Power BI Service, open a report → Click “Analyze in Excel”.
• Step 2: Open the downloaded .odc file in Excel.
• Step 3: Use PivotTables, Formulas, or Charts with live-connected data.

Who Should Use This Method?

The “Analyze in Excel” method is ideal for:

• Business analysts who prefer Excel’s flexibility but need enterprise data.
• Finance teams doing ad-hoc analysis on centralized datasets.

Ideal Use Case:

• A CFO reviewing Power BI financial data in Excel for custom variance analysis.

Will You Need a License to Use This Method?

Yes, you’ll need Power BI Pro/Premium (for both the report creator and viewer) to use this method. This is because it requires Power BI Service, which is not included in the free plan.

3. Exporting Power BI Data to Excel for Further Analysis

If you want to use your Power BI data in a raw format for customized modeling, you can use this method. It’ll help you export Power BI data to Excel for analysis.

To do so, follow this simple two-step process: 

• Step 1: In a Power BI report, click “Export Data” on a visual.
• Step 2: Choose between: 

  – Summarized Data: Static snapshot (free).

  – Underlying Data: Refreshable table (Pro/Premium).

   

Who Should Use This Method?

The “export to Excel” method is ideal for: 

• Data scientists who need raw data for advanced modeling.
• Teams without Power BI access who rely on Excel.

Ideal Use Case:

• Exporting customer segmentation data from Power BI to Excel for statistical analysis.

Will You Need a License to Use This Method?

You can use this method for free if you only want to export the summarized report. However, you’ll need a Pro/Premium licnese to export the underlying data.

 

How to Use Power BI with Excel: 5 Best Practices

1. Optimize Data Structure

To optimize your data structure, use Excel Tables instead of ranges.

Here’s how it can help you:

• Tables (Ctrl+T) maintain structured references, preventing errors when data expands.
• Power BI recognizes tables as single entities, making refresh operations more reliable.

Following this practice will ensure that you never suffer from broken connections when adding new rows/columns to your Excel source files!

2. Leverage Power Query for Data Cleaning

Always remember to clean your data to remove duplicates, fix errors, and standardize formats before importing.

Here’s why this is important:

• Power Query’s non-destructive editing preserves raw data while creating clean outputs.
• Transformations apply automatically during refreshes (unlike manual Excel cleaning).

So, if you invest your time in cleaning your data, you can save hours of repetitive work and maintain consistent data quality across reports.

 

3. Use Power BI for Dashboards, Excel for Ad-Hoc Analysis

Here’s a general rule that data visualization consultants follow:

• They use Power BI for creating enterprise-grade reports.
• They leverage Excel to perform custom calculations and run what-if scenarios.

This is because:

• Excel’s formula flexibility is perfect for one-off calculations and sensitivity analysis.
• Power BI handles large datasets and real-time updates better than Excel.

In other words, by using the right tool for the right exercise, you can prevent crashes with big data while retaining analytical versatility.

 

4. Schedule Automatic Refreshes

Another way to benefit from Power BI Excel integration is to set up scheduled refreshes in Power BI Service for real-time insights.

Here’s why:

• You might get outdated insights into your data if you rely exclusively on manual updates (e.g., stale inventory numbers).
• Plus, Premium licenses allow up to 48 refreshes/day (vs. 8 with Pro).
  

So, you can benefit from leveraging scheduled/automated refreshes without manual intervention. This can be especially critical for your ops/finance teams. It’ll give them real-time updates and information whenever they need them!

5. Apply Row-Level Security (RLS)

Lastly, you should use Power BI’s security features to restrict data access to specific users.

I primarily recommend this practice because Excel lacks native security, so anyone with file access will be able to see all the data within it.

That’s where Power BI RLS restricts data visibility by user role (e.g., regional managers see only their territory).

This way, you can safely share reports without exposing confidential information while also eliminating the need to share them via email or other potentially unsafe communication channels.

You’re Ready to Maximize the Combination of Power BI with Excel

Power BI and Excel are great data visualization tools. However, both of them come with their own limitations. While it’s harder to perform data modeling and custom calculations with Power BI, Excel’s performance lags can be a serious problem for anyone handling million+ rows.

That’s why I highly recommend using them together: this way, they’ll compensate for each other’s limitations and empower you to enjoy the best of their capabilities.

However, you might not be an expert in both Power BI and Excel.

That’s where we come in!

At Augmented Systems, we specialize in helping you leverage the best of both worlds by bridging your knowledge gap with our technical expertise.

We’ve had great success in helping several clients combine their Power BI and Excel workshops into one smooth operation. So, whether you need more speed, security or sophisticated analysis, we offer data visualization services that suit all use cases.

Connect with our data visualization consultants and experience the difference that the Power BI Excel integration can make to your operations!

How to Use Power BI with Excel: FAQs

1. Can I use Power BI with Excel for free?

Yes! Power BI Desktop is free for importing Excel data and creating reports. However, sharing dashboards or using “Analyze in Excel” requires a Pro/Premium license.

2. When should I use Excel vs. Power BI?

Use Excel for quick calculations and small datasets (<1M rows). Switch to Power BI for big data, real-time dashboards, and advanced visuals.

3. How do I stop Excel from crashing with large Power BI datasets?

Use Power BI’s “Analyze in Excel” feature. It keeps data in the cloud while letting you analyze it in Excel without loading everything locally.

4. Can I automate data updates between Excel and Power BI?

Absolutely! Set up scheduled refreshes in Power BI Service (up to 48/day with Premium) to keep Excel-connected reports current.

5. Is my data secure when sharing between Excel and Power BI?

Yes! Power BI’s Row-Level Security (RLS) lets you control who sees what, unlike Excel, where anyone with the file sees everything.

Good companies collect data, but the great ones make it work for them!

As a modern executive, data analyst, or even a team leader, you can’t make any decision unless it’s backed by data. That’s how you can be certain that your decision isn’t just based on a good instinct, but is actually backed by good data!

But that’s where the problem starts – you have so many sources of data:

• CRM tools
• Cloud databases
• SaaS Platforms
• Third-party APIs 

So, how can you successfully connect them to your Power BI ecosystem and get the actionable insights you need to drive smarter decisions?

By using Power BI connectors that act as a bridge between your data and Power BI’s robust data modeling engine.

In this article, I’ll tell you what Power BI connectors are, their types, and the best ways to use them.

What are Power BI Connectors and Their Types: Table of Contents 

• What are Power BI connectors?
• Why are Power BI Data connectors important?
• What are the types of Power BI connectors?
• How to use a Power BI connector?
• 5 best practices for using Power BI connectors
• Every dataset deserves the right connector!
• Power BI Connectors: FAQs

What Are Power BI Connectors? 

A Power BI connector is exactly what it sounds like. It’s a built-in solution that connects Power BI to any specific data source.

Basically, it lets your dashboards connect directly with your:

• Databases
• Cloud platforms
• Data repositories
• SaaS tools

Power BI current has over 200 connectors available and can extract and load data from sources like:

• SQL Server
• Google Analytics
• Azure Data Lake
• Excel sheets

Also read: The Top 10 Power BI features.

Why are Power BI Data Connectors Important?

Most businesses today work with data spread across many platforms. This makes it hard to bring everything together in one place. That’s where Power BI data connectors help.

It allows you to bring in data from various tools without requiring complex setups. This gives you a whole suite of benefits, which are as follows:

• You don’t have to jump between tools anymore, as it consolidates everything into one report.
• Data refreshes on its own. No exporting, no uploading. 
• Cleaning stuff like weird headers or extra rows? A lot easier now.
• Everyone’s looking at the same thing, so there’s less confusion or overlap.
• There’s no need to involve a developer team just to connect systems.

Simply put, the connector handles the technical aspects. You can simply review the insights and proceed with the actual work.

What are the Types of Power BI Connectors? 

Microsoft keeps adding to its list of connectors, so whether your data’s in a spreadsheet, a cloud tool, or a big enterprise database, you’re probably covered.

These connectors usually fall into three general types:

1. Native Connectors

Native connectors are the built-in tools that come with Power BI. Microsoft develops these, and they are ready to use, requiring no setup or additional software.

They allow you to bring in data from common sources, such as files, databases, and online services.

Here are the main types of native connectors:

 

File Connectors

These connectors enable Power BI to integrate with file types, such as:

 

• Excel
• CSV
• XML
• JSON
• PDF 

If you store reports or logs in files, you can easily upload them and start building visuals in minutes.

 

Database Connectors

With database connectors, you can connect to popular databases, including:

 

• SQL Server
• MySQL
• PostgreSQL
• Oracle
• Snowflake 
• Google BigQuery. 

Power BI will pull your data directly from these systems, either by importing it or reading it live.

Online Services Connectors

These are used to connect to platforms such as:

• SharePoint
• Dynamics 365
• Salesforce
• Google Analytics
• Microsoft Exchange

Other Connectors

Sometimes, you might need to bring in data from places like:

 

• Azure Blob Storage
• A web API
• An OData feed

These may not be the standard data sources you typically work with. Power BI has connectors for them, too.

So, no need to dive into complex code; just connect it, and Power BI takes care of the rest. Your data shows up, ready to work with.

When are these connectors helpful?

• Working with everyday file types like Excel or CSV? These connectors handle them with no extra setup.
• Need to pull data from SQL Server or Oracle? You can do that with no custom coding.
• Do you have dashboards running on Salesforce or Google Analytics? Power BI connects to them in just a few clicks.
• Since they are built and maintained by Microsoft, updates and security features are part of the package.

2. Third-Party Connectors

Sometimes, Power BI doesn’t have a built-in connector for the tool or platform you’re using. In such cases, third-party connectors come into the picture.

Third-party connectors are created by external companies (not Microsoft) to help Power BI connect to their own systems or services.

These connectors work just like the built-in ones. They let you bring your data into Power BI, but they’re developed and maintained by trusted Microsoft partners or software vendors.

For instance:

• You might be using tools like Zoho CRM, HubSpot, or SAP Business One, and Power BI doesn’t have a built-in connector for those.
• Sometimes, the company behind the tool has its own connector. 
• A third-party developer also might’ve built one that you can just install and start using.

Generally, you’ll find third-party connectors in the Power BI Connector Gallery.

 

When are these connectors helpful?

• When you’re working with niche or industry-specific software.
• If you want to connect to tools that Power BI doesn’t yet support natively.
• When you need customized integration with a particular app.

3. Custom Connectors

There might be instances when your team wants to integrate with a tool that Power BI can’t connect to, neither natively nor through third-party add-ons.

In such scenarios, custom connectors in Power BI do the job.

They’re built using Microsoft’s Power Query SDK and the M language, which lets Power BI pull data even from internal tools or private APIs.

How Custom Connectors Work?

I’ll tell you in a very clear manner how these connectors work:

 

• Create the Connector: It starts with writing an M script using the Power Query SDK, usually in Visual Studio or VS Code.
• Set up Logic: The script instructs Power BI on how to access your data source. That might mean signing in, dealing with paged results, or shaping the raw data into something you can actually work with.
• Package and Deploy: The output is a .mez or .pqx file. Place it in your Power BI Desktop’s Custom Connectors folder, then enable custom extensions in settings.
• Use in Power BI: The connector appears in the Get Data menu. You enter credentials, select the tables or fields, and load the data, just like any native connector.

When are these connectors helpful?

• When your data lives in an internal API, or there’s no connector you can buy.
• When you want a branded, easy-to-use connector for your team.
• When built-in features don’t support advanced tasks, such as OAuth authentication or pagination.

How to Use a Power BI Connector?

Using a Power BI connector isn’t a very technical task. Instead, it’s quite easy, and I’ll tell you how you can get started:

• First, open Power BI Desktop. 
• Click on “Get Data” from the Home tab. 
• You’ll see a list of available connectors.
• Choose one, such as SQL Server or Salesforce. 
• Now, you’ll need to sign in with your credentials to set up a secure connection.
• Once that’s done, just pick the tables or fields you want to import.
• You can then use Power Query to refine the data, such as filtering rows, renaming columns, or reshaping the data as needed.
• When it looks right, load it into Power BI and start building your Power BI dashboards.

5 Best Practices for Using Power BI Connector

These are some of the best practices that you can follow when using Power BI Connectors.

1. Choose the Right Connection Mode

Power BI offers three modes: Import, DirectQuery, and Live Connection.

• Use Import for faster performance with static or small datasets.
• Choose DirectQuery when you need real-time or near-real-time data.
• Use Live Connection with services like Azure Analysis Services for dynamic models.
  

2. Filter Data at the Source

Don’t pull in entire tables.

Apply filters during query setup or at the SQL level to reduce load time and improve performance.

Less data means faster refreshes and a more responsive report.

3. Limit Columns and Tables

Only import the fields and tables you actually need.

Unused columns increase file size and slow down the data model. A lean data model leads to better report performance and easier maintenance.

4. Use Parameters for Flexibility

Use parameters to define items such as server names, file paths, or API keys.

It will help you in making your reports:

• Easier to reuse
• Safer to share
• Simpler to manage

Especially when moving between dev, test, and production.

 

5. Monitor and Optimize Data Refresh

Set your data refresh frequency according to how frequently your data changes.

Avoid overloading source systems with unnecessary refreshes, and monitor failures via the Power BI Service refresh history.

Pro Tip: If all this seems too technical to you or you don’t want to manage it yourself, you can get in touch with a trusted data visualization consultant. They’ll know the technical ins and outs and can make your Power BI reports truly actionable and performance-optimized.

Every Dataset Deserves the Right Connector!

By now, you have explored a wide range of Power BI data connectors, where each serves different needs depending on the type of data you use and your reporting goals.

Now, choosing between them will require you to have a strong data integration strategy.

That’s where we can help!

 

At Augmented Systems, we empower organizations to harness the potential hidden within their data through our database services, which include:

• Data Migration
• Data Analytics
• Data Visualization
• Data Warehousing

It means we can help you choose and implement the best connector strategy for your reporting needs.

So, if you’re unsure which connector suits your needs, let our data visualization consultants guide you…

We’ll help you connect the dots efficiently, accurately, and without the usual complexity!

What are Power BI Connectors and Their Types: FAQs

1. What are Power BI connectors used for?

Power BI connectors serve as a bridge, enabling Power BI to connect to a vast range of data sources. They are used for:

• Data integration
• Data Visualization
• Real-time data access
• Accessing diverse data sources
• Scalability

2. How many types of Power BI connectors are there?

There are three main types of Power BI connectors, which are:

 

• Native Connectors: Built by Microsoft.
• Third-Party Connectors: From external vendors.
• Custom Connectors: For specific or unsupported data sources and APIs.

3. Are Power BI connectors free to use?

Most native Power BI connectors are free with Power BI Desktop. However, some third-party connectors or premium features may require a Power BI Pro or Premium license.

 

4. How do I troubleshoot Power BI connector errors?

To troubleshoot Power BI connector errors, these are the things you can follow:

• Start by checking the error message
• Validate credentials
• Ensure the data source is online
• Use Power Query diagnostics
• Review gateway settings 
• Update Power BI Desktop to the latest version

5. Are Power BI connectors secure for enterprise use?

Yes, Power BI connectors are secure for enterprise use as they support secure protocols like:

• OAuth 2.0
• Azure Active Directory
• Encrypted data transfer