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Tableau vs. Excel: Which One Should You Choose for Data Visualization?

The debate between Tableau vs Excel poses a challenge for budding data scientists. While Excel has dominated the spreadsheet market for over 40 years, many people are unsure whether to continue using it or switch to Tableau.

It’s natural to feel dilemmatic by the choices available in data visualization tools. Excel is effective for data management. However, Tableau’s arrival raises questions about its competitiveness, making it hard to choose the best fit for your needs.

 

Acknowledging the unique strengths of both tools is essential to addressing this challenge. Excel is ideal for performing calculations and preparing data, while Tableau excels at visualizing complex datasets and presenting interactive reports.

Understanding each platform’s advantages can effectively enhance your analytical capabilities.

 

Let us begin by quickly understanding What is Data visualization in brief.

Tableau vs Excel – Table of Contents

  • What Is Data Visualization?
  • Overview of Tableau
  • Overview of Excel
  • What are the Key Differences Between Tableau and Excel?
  • Tableau with Excel: How Both Can Work Together?
  • Tableau vs Excel: Who Wins the Race of Data Visualization?
  • Frequently Asked Questions

What Is Data Visualization?

Data visualization is a graphical presentation of data, enabling the identification of trends, patterns and insights.

 

It simplifies complex datasets, helping you make informed decisions. This visual approach allows you to understand and interpret the data easily, enhancing your ability to grasp important information efficiently.

 

Technology growth has made many data visualization tools to help you visualize easily. Tools such as Tableau, Power BI, Excel, Looker, Qlik and Infogram are prominent in the data visualization landscape.

 

However, I will compare two prominent data visualization solutions in the section below: Tableau and Excel.

 

Let’s begin by understanding both of them in brief.

Overview of Tableau

Tableau is a Business intelligence tool that helps you create and visualize interactive dashboards in a few clicks.

It sets correlations apart using color, size, labels and shapes, thus giving them an additional context to gain information.

 

In a nutshell, this BI solution lowers the knowledge barriers to allow you to visualize data even if you are a non-technical individual. To understand how Tableau benefits over Excel, it is important to understand its advantages and disadvantages.

What are the Advantages of Using Tableau?

Tableau, being a new-age data visualization solution, provides you bunch of benefits, some of which are mentioned below:

  • Tableau Dashboards has an outstanding reporting feature that offers convenient dashboard customization. However, this feature can only be used on mobile phones or laptops.
  • Further, Tableau can easily integrate with other technologies like Python or R to help you perform complex calculations.
  • Lastly, it can handle a large amount of data.

 After understanding Tableau let us have a brief about what is Excel?

Overview of Excel

Microsoft Excel is a spreadsheet application that performs calculations, statistical operations, data analysis and reporting. It stores data in rows and columns.

This data is usually managed in boxers made by the intersection of rows with columns as cells.

You can add tables, charts, graphics, and other visualizations depending on your specific needs to make the spreadsheet more informative and presentable.

Let’s understand the advantages of Excel to check out how it benefits over Tableau.

What are the Advantages of Using Excel?

Although Excel is one of the oldest data visualization tools, it still manages to provide some noteworthy advantages, which are as below:

  • Excel can analyze large amounts of data to identify trends to help you make an informed decision.
  • Moreover, it also performs tons of mathematical and logical functions easily.

Going ahead, let us check the difference between Tableau and Excel.

What are the Key Differences Between Tableau and Excel?

Tableau vs Excel has always been a famous battle when discussing the best data visualization tools.

 

Both these data visualization solutions have unique features, which we learn in this section.

The following table will help you understand the difference between Tableau and Excel to help you choose the best one.

Features

Tableau

Excel

Data Visualization

Designed for visualizing and exploring data

Offers some basic visualization features like charts and graphs.

Data Preparation

Limited, but it can connect with tons of data sources

Extensive, with data cleaning, transformation and modeling features

Data Analysis

It is more advanced with features like data blending and forecasting

It is basic but offers pivot tables and statistical functions

Collaboration

Allows you to collaborate on data analysis and real-time sharing

Limited collaboration possibilities with basic features like sharing and tracking changes

Cost

A paid software offering different pricing plans

It is a part of the Microsoft Office suite subscription

Learning Curve

The learning curve is steeper with some knowledge of data analysis needed

The knowledge curve is relatively low as it is widely used and familiar

Data Blending

You can easily blend data with other data sources

Data is limited to the workbook and does not allow for easy data blending

Scalability

Designed for large-scale data analysis and visualization

Offers limitations with large amounts of data and complex structure

Interactive Dashboards

Known for its ability to create highly customized and interactive dashboards.

Limited to creating static reports and charts.

Performance

Can manage large volumes of data and offer high performance

It can manage large datasets and perform complex calculations but is relatively slow.

Platform

Runs on Windows and Mac OS

Runs on Windows, Mac OS and web-based platforms

Data Security

Offers role-based and row-level security options

Offers limited data security options and is generally more vulnerable

Data Connectivity

Supports connectivity with a wide range of databases

Offers limited support for data connectivity

 

Can you use Tableau and Excel together after covering the difference between Tableau and Excel?

The simple answer: is yes. As a Data Migration consultant, I believe Tableau and Excel can offer great results if used together.

 

Check out the below section to know how to make them work together.

Tableau with Excel: How Both Can Work Together?

When used together, Tableau and Excel can be powerful tools. Below is a detailed look at how they can produce efficient results.

3 Quick Steps to Make Tableau and Excel Work Together

1. Connect To Excel

  • Open Tableau and Select Excel under the connect section.
  • Then, choose the desired Excel workbook and click open.
  • You can rename the data source for clarity on this page and select the specific sheets to analyze data.

2. Data Handling

  • Tableau easily connects with multiple Excel sheets.
  • Custom SQL queries can focus on specific data instead of the entire workbook.

3. Data Preparation

  • Tableau offers a Data Interpreter feature that helps you clean and optimize data for analysis by identifying sub-tables and removing problematic formatting.
  • Moreover, you can set options for how field names are treated to ensure that data is accurately presented in Tableau.

After learning how to use Tableau and Excel together, let’s consider the advantages of this collaboration.

What are the Advantages of Using Tableau with Excel?

  • Tableau converts raw Excel data into visuals, making it easy to understand trends and insights without extensive reporting.
  • The drag-and-drop functionality of Tableau simplifies the creation of visual analysis that allows you to work on their findings.
  • Visuals created in Tableau can be easily shared across teams, encouraging collaboration and enabling stakeholders to access insights directly.

Lastly, let us check out the Common Use Cases of Tableau with Excel.

2 Common Uses of Using Tableau with Excel

  • You can merge multiple Excel sheets into one cohesive dataset with Tableau, thus helping in more complex analysis.
  • While Excel is widely used for data management, it has limitations regarding visualization capabilities. Tableau addresses these shortfalls by offering advanced analytical features to enhance decision-making.

Tableau vs Excel: Who Wins the Race of Data Visualization?

The selection of data analysis and visualization tools depends solely on your needs and situation. Excel is a low-cost, versatile tool that should be your first choice for working with small to medium-sized datasets.

Alternatively, Tableau should be the best choice if you’re looking for advanced visualization and want to integrate multiple data sources.

Choosing between Excel and Tableau for data visualization requires careful strategy and planning; if developing that plan feels challenging, consider seeking guidance from the best consultants for data visualization.

Frequently Asked Questions

1. Why do companies use Tableau?

Companies choose Tableau due to its intuitive interface and capability to generate insightful data. Tableau helps Data Scientists and Business Analysts enhance their company’s decision-making. Moreover, it facilitates efficient data loading, analysis and clear presentation for stakeholders. 

2. Does Tableau have a row limit like Excel?

No, unlike Excel, Tableau doesn’t have any limit for rows. Using Tableau aids professionals save their time and instead draw attention to the data that matters. Moreover, Tableau might have numerous advantages over Excel.

3. Which tool is better for data visualization – Tableau or Excel?

 

After using both Tableau and Excel, I found that Tableau is more suited to diverse, interactive and customizable data visualization. On the other hand, I thought that Excel provided more basic charts and may be suitable for straightforward data representation. In particular, Tableau excels at creating complex and interactive dashboards.

Choosing the right data visualization tool requires a thorough data visualization tools comparison to ensure the best fit for your specific needs.

Categories
Blog Data Visualization

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

Are you leaving money on the table? In today’s data-driven world, you will fall behind if you don’t leverage advanced data analytics.

You might miss crucial insights and make decisions based on your gut feelings instead of the facts.  These decisions taken based on guts might drop your productivity gains.

Feel like you’re not getting the most out of your data? Trust me, I get you. 

As a Data Analyst, I’ve been in trenches, fighting with the same question: “Which are the best data visualization tools?”

However, Power BI and Excel are two of the best tools available.

The decision to work with one of these two can feel overwhelming. This decision can either make or break your ability to turn raw data into actionable insights.

In this blog, I’ll do the necessary groundwork to help you choose the best by comparing Power BI vs Excel.

Power BI vs Excel: Table of Contents

  • Overview of Power BI
  • Overview of Excel
  • Differences Between Excel vs Power BI
  • Benefits of Power BI Over Excel: How it Holds the Upper Hand?
  • Benefits of Excel vs Power BI: How it Holds the Upper Hand?
  • Why use Power BI: 3 Deciding Points to Know
  • Why use Excel: 3 Deciding Points to Know
  • Power BI vs Excel: Who Wins the Race?
  • Frequently Asked Questions

Overview of Microsoft Power BI

Microsoft Power BI is one of the popular business intelligence and big data visualization techniques and tools that transform raw data into interactive dashboards.

It helps you get enterprise-level insights for informed decision-making.

Core Functionalities of Power BI

1. Visualization

You can create intuitive reports using the drag-and-drop option offered by Power BI. Moreover Power BI also allows you to build visuals using a variety of customizable visuals.

2. Data Integration

Power BI allows you to connect with diverse sources like databases, cloud services and Excel files.

3. Collaboration and Sharing

Using Power BI, you can share insights across organizations using web and mobile apps to enable data exploration.

4. Intelligent Analytics

For efficient data analysis, you should use embedded AI features like Natural Language query, anomaly detection, and automated insights.

Overview of Excel

Microsoft Excel is a widely used spreadsheet application in the Microsoft Office suite. It helps you organize, analyze and store data.

It helps you present the data in a tabular format and is suitable for various tasks, from basic data entry to complex statistical analysis.

Core Functionalities of Excel

1. Data Management

One of Excel’s best features is “Data Management,” which allows you to organize and store data within spreadsheets using rows and columns.

2. Calculations

You can also use the built-in formulas to perform various calculations, derive insights, and automate repetitive tasks.

3. Visualizations

Using Excel, you can create charts and graphs to visually represent data and communicate the findings effectively.

4. Customization

Lastly, Excel’s pre-built templates can be used for common tasks and VBAs to develop custom solutions.

Next, let us understand the difference between Excel and Power BI.

Difference Between Excel and Power BI

Feature

Power BI

Excel

Data Handling/Capacity

Handles millions of rows efficiently. Connects directly to data warehouses and cloud sources

Limited to approximately 1 million rows. Struggles with performance on larger datasets

Data Visualization

It is designed for dynamic and interactive visualizations

Primary statistics charts and graphs in Excel present data

Data Sources

Can combine data from multiple sources, including the cloud platforms

Limited in the number of data sources it can merge with

Customization & Flexibility

It is less flexible and offers some pre-defined report templates

It offers a high level of flexibility and customization and complete control over formatting, styling and graphical elements

Ease of Use

Power BI has a more intuitive interface for data visualization but needs training for advanced features

Excel is simple and easy to use, especially for simple tasks

Processing Speed

Power BI offers faster processing than Excel

Excel offers slower processing than Power BI

 

Let’s talk about the benefits of Power BI over Excel.

Benefits of Power BI Over Excel: How it Holds the Upper Hand?

Power BI offers many benefits, but the below benefits hold the upper hand against Excel.

1. Handles Large Datasets

You can manage and analyze massive amounts of data, even with millions of rows. Power BI uses a compression algorithm to import cache data to help you analyze large datasets.

2. Real-Time Data Insights

Power BI can connect with vast data sources to provide up-to-the-minute analytics and dashboards. Moreover, it can automatically refresh reports and visualizations when new data comes in to serve you with the latest insights.

3. Interactive Visualizations

One of the vivid features of Power BI is its dynamic, interactive and linked visualizations. You can filter, sort and navigate between visuals to identify data from different angles to gain deeper understanding.

4. Collaboration

Lastly, Power BI provides superior collaboration features compared to Excel, thus allowing you to share dashboards and reports. Its cloud-based services enable collaborative data analysis across organizations.

This was about the benefits of Power BI over Excel, but do you know how conventional data visualization tools like Excel ace over Power BI?

 

In the below section, I’ll talk about the benefits of Excel over Power BI.

Benefits of Excel Over Power BI: How it Holds the Upper Hand?

Excel offers many benefits, but the below benefits of Power BI hold the upper hand against Power BI.

1. Flexibility and Customization

Excel offers great flexibility and customization. You can completely control formatting, styling and data arrangement, allowing you to design Excel spreadsheets for specific needs and use cases.

2. Familiarity

Excel is a more common and familiar tool for many users thus making it a handy tool. Its simplicity and familiarity make it easy to work with data in spreadsheets.

3. Ease of Use for Smaller Datasets

Out of all data visualization tools, Excel is more intuitive for simple tasks and is well-suited for ad-hoc analysis. Moreover, Excel can enable data manipulation and analysis on a smaller scale.

4. More Operations with Data

Lastly, Excel offers more operations with data than Power BI. Simply put, it has more diverse functionality and is the go-to choice for expert data analysis.

While discussing the difference between Excel and Power BI, I would also like to highlight why you should use Power BI instead of Excel.

Why Use Power BI Over Excel: 3 Deciding Points to Know

Microsoft Power BI is a data analytics and reporting tool that helps you visualize raw data and present actionable information.

Below are the five reasons to use Power BI over Excel:

1. High-Level Analytics

Power BI excels at offering comprehensive business analytics, making it easier to identify trends and insights in data.

It is more feasible for enterprise-level data to offer responsive visualization and modeling.

2. Real-Time Data Analytics

Being a modern-day data visualization tool, Power BI can connect live data sources to offer up-to-the-minute information and insights.

3. AI Integration

Power BI brings together AI and Business intelligence through its Quick Insights Tools. With this powerful blend analysis, you can gain better insights into your data.

Now that we’ve discussed why you should use Power BI instead of Excel let me explain why you should use Excel instead of Power BI.

Why Use Excel Over Power BI: 3 Deciding Points to Know

1. Cost and Accessibility

Excel is part of the MS Office Suite, which makes it more readily accessible and cost-effective for users.

2. Ad-hoc Analysis and Calculations

Excel is beneficial for ad hoc analysis and calculations. It can also organize data, transform it and perform mathematical operations.

3. Smaller Datasets

As a data visualization tool, Excel is more effective for manipulating and formatting smaller datasets. Its workbook can load up to 1 million rows and 16,000 columns per worksheet.

Power BI vs Excel: Who Wins the Race?

When we talk about Data visualization, both these data visualization tools are useful in different areas.

Power BI is the best choice for large companies working with large amounts of data and creating interactive charts.


I recommend Excel if you’re dealing with a small amount of data and need to make frequent changes.

 

Choosing the best between Power BI and Excel depends on your needs. Knowing what each one does best can help you use the data effectively.

Frequently Asked Questions

1. What’s the main difference between Power BI and Excel for handling data?

Power BI is better at handling large amounts of data (up to 1 million rows). However, if you have limited data, I recommend using Excel.

2. Which is better for making charts: Power BI or Excel?

Power BI is great if you want to experiment with different types of charts for your data and visualize it in real-time. However, Excel is a good option if you want simple but visually appealing charts.

3. When should I use Excel instead of Power BI?

Excel is a good choice when you need to make changes easily, work with smaller amounts of data, or perform quick calculations. It is also cost-effective, especially if you already use Microsoft Office.

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Blog Data Visualization

Power BI vs. Looker: Choosing the Right BI Tool for Your Needs

Business Intelligence and data visualization are key in visualizing data.

That is why you need to know which tools you’re working with!

For instance, Looker Studio and Power BI are two important business intelligence tools.

Microsoft develops the reporting and analytics features provided by Power BI, while Google Cloud develops Looker Studio, a BI tool.

In this article, I’ll discuss the differences between Power BI and Looker to help you select the best tool.

Let’s get started!

Power BI vs Looker: Table of Contents

  • Business Intelligence Tools: What are they?
  • Overview of Power BI
  • Overview of Looker
  • What Are the Differences Between Power BI vs Looker
  • Power BI vs Looker: Pricing Comparison to Consider
  • When to Choose Power BI and Looker?
  • Choose the Best Tool That Fits Your Needs!
  • Power BI vs Looker: Frequently Asked Questions

Business Intelligence Tools: What are they?

Before discussing Power BI vs Looker, let’s quickly understand the role of business intelligence in modern business.

Business intelligence tools are designed to gather, analyze, and visualize data from various sources.

Implementing data visualization best practices to make informed decisions becomes easy when you have the right tools.

These tools allow businesses to transform raw data into actionable insights, which can help them gain a competitive edge.

Although various Business intelligence tools are available, the comparison of Power BI vs Looker is crashing the records.

First, let’s talk about Power BI.

Overview of Power BI

Power BI, which Microsoft developed, is a popular self-service BI tool.

The tool offers a broad range of features for data analysis and visualization. 

Its strong integration with Microsoft products and services makes it a compelling choice for organizations that use the Microsoft ecosystem.

Designed for power users and businesses that require deep data insights, Power BI can integrate with Microsoft products such as Excel, Azure and Teams.

Key Features of Power BI

Data visualization tools comparison would always be incomplete without comparing the features of BI tools.

Below are some features that make Power BI one of the best data visualization tools.

  • Tools like Power Query and DAX enable in-depth data transformation and calculation.
  • Can connect with 100 data sources, including cloud services, on-premises databases and third-party platforms.
  • Microsoft AppSource allows you to create unique visuals in addition to the many built-in visuals.
  • Security and scalable reporting for big businesses.

Further, let’s understand the Pros and Cons of Power BI.

Pros and Cons of Power BI

As with any BI tool, Power BI has strong and weak points. Below are the Pros and Cons of Power BI  that you should consider:

Pros of Using Power BI

  • Power BI’s integration with Microsoft products makes it a natural choice for organizations that use the Microsoft ecosystem.
  • Moreover, it offers a wide range of visualizations, thus allowing users to create compelling reports and dashboards.
  • Its AI power enables users to uncover the data’s hidden patterns, trends and outliers.

Cons of Using Power BI

  • Power BI’s data modeling capability can be complex for users unfamiliar with the Microsoft ecosystem.
  • Power BI allows sharing and collaboration, yet its area is less efficient than other tools.
  • Lastly, its licensing option and cost can differ based on the features and level of access needed.

Further, let’s talk about Looker Studio.

Overview of Looker

Looker Studio is a leading cloud based business intelligence software that offers a wide range of analytics and data exploration capabilities.

The tool is well-known for its user-friendly interface and powerful data modeling ability.

Designed for simplicity and real-time analytics, Looker Studio can seamlessly integrate with Google tool suites like Google Ads and BigQuery.

Below are some features that make Looker Studio one of the best cloud based business intelligence software.

Key Features of Looker

While doing a Data visualization tools comparison, the features offered by each of them play an important role. 

Let’s check out the features offered by Looker.

  • Intuitive for beginners and is non-technical for users.
  • Can easily connect with Google tools and third-party data sources via connectors.
  • Allows multiple users to edit and share reports in real-time.
  • Looker is free for individuals and small teams, thus making it highly accessible.

Further, let’s understand the Pros and Cons of Looker.

Pros and Cons of Looker

Similar to any BI tool, Looker has its strengths and limitations. Below are the pros and cons of Looker to consider:

Pros of Using Looker

  • Looker’s intuitive feature can make data analysis easy without needing technical skills.
  • The data modeling ability of Looker enables complex data transformation and ensures data consistency.
  • Users can seamlessly collaborate on dashboards and reports, share insights and schedule automated data delivery.

Cons of Using Looker

  • Despite being user-friendly, you might need to spend some time mastering all the features of Looker.
  • Although Looker’s data visualization ability is adequate for many use cases, it might not offer the same ease of use as other tools like Power BI.
  • It is more expensive, particularly for small businesses or organizations with limited budgets.

Let’s check out the differences between Power BI and Looker.

Differences Between Power BI vs Looker

Point of Comparison

Power BI

Looker

Data Visualization

Focuses on customized data visualization with detailed analytics

Focuses on simple and easy-to-use visualizations

Data Integration

Can easily integrate with other Microsoft products and services

Its data modeling feature lets you integrate data from multiple sources

Customization

Extensive customization options for visualization that allow you to build tailored reports and dashboards

Allows customization at data modeling levels, enabling you to apply business logic

Security

Multiple repositories that allow you to store and manage data

Its AES 256-bit encryption enables efficient data security

Furthermore, let’s analyze the pricing differences in detail when comparing data visualization tools.

Power BI vs Looker: Pricing Comparison to Consider

Power BI Pricing

Although the free version of Power BI offers data connectivity for simple datasets, users must buy a paid subscription to use the advanced features.

Power BI offers paid subscriptions starting around $10 per user/month for the Pro license.

Looker Pricing

The basic version of Looker Studio is completely free and can be easily accessed by small businesses.

Looker also has a pro version, which offers team workspaces and enterprise-level customer support via Google Cloud Customer Care.

Additionally, there is a fee if you use third-party data connectors to import data into Looker Studio.

Further, let’s check out the use cases of Power BI and Looker.

When to Choose Power BI and Looker?

Opting between Looker Studio and Power BI depends on your organization’s needs, budgets and technical know-how.

These tools are excellent but shine in different cases and situations.

Check out the below section to know when to use Looker vs when to use Power BI.

Looker is Best For:

  • You’re running a small or medium business that needs an affordable, user-friendly tool to create visually appealing reports.
  • You need real-time data visualization for marketing and website analytics with minimal technical skills.
  • You need a tool that allows multiple users to edit and share easily.

Power BI is Best For:

  • You’re a large organization or enterprise with complex reporting requirements.
  • Scalability and enterprise-grade features are important for handling large volumes of data.
  • You need a dedicated data team or technical experts who can fully use Power BI’s advanced features.

Choose the Best Tool That Fits Your Needs!

Both Power BI and Looker are highly recommended data visualization tools.

Implementing a successful data visualization process can be daunting. However, selecting the best one depends on particular use cases and requirements.

Looker is popular for its efficient modeling capability to handle large datasets.

Power BI provides a user-friendly interface and seamless integration with other Microsoft products.

Frequently Asked Questions

1. Is Looker as good as Tableau?

Looker is often compared with Tableau. While Tableau may have a more intuitive interface and larger user base, Looker stands out for its efficient data modeling ability to create custom reports designed to specific business needs.

2. What are some other tools similar to Power BI?

As a Data Migration Consultant who likes Looker, I also know the value of a good deal! In addition to Tableau and Qilk Sense, consider these budget-friendly Power BI alternatives: Zoho Analytics is easy to use and priced well, and Metabase is a free, open-source option. These offer solid features without breaking the bank!

3. What should I consider when choosing between Power BI and alternatives?

When choosing a BI tool, consider the following:

 

  • Data Sources: Can it connect to your existing data?
  • Ease of Use: Is it user-friendly for your team’s skill level?
  • Visualization: Does it offer the charts and graphs you need?
  • Pricing: Does it fit your budget?
  • Support & Training: Is there good documentation and support available?
Categories
Blog Data Visualization

7 Easy Steps to Create Dashboards in Power BI

Overview

This quick Power BI dashboard tutorial outlines the essential workflow for building dashboards in Power BI:

  • Step 1: Connect to your data source (like Excel).
  • Step 2: Build a data model with table relationships.
  • Step 3: Create a report using data visualization tools (charts, graphs).
  • Step 4: Pin those visuals to a new dashboard.
  • Step 5: Enhance and customize the layout and theme.
  • Step 6: Share the dashboard with your team.
  • Step 7: Maintain and improve with refreshes and interactivity.

In this blog, I will break down all 7 steps in detail to help you build your first Power BI dashboard.

If you’ve been sitting in front of the Power BI interface while wondering how to get started, you’re not alone!

Power BI is one of the most powerful data visualization tools out there. And interactive dashboards are one of its core strengths.

But to build dashboards in Power BI? You will have to go through a steep learning curve! It’s slightly tricky to get started, but once you’ve got the hang of it, you will become an expert in no time!

However, the first step is always the hardest, and that’s exactly what I’m here to help you with in this step-by-step Power BI dashboard tutorial.

I will break down each and every step into a clear action you can take, and guide you through the process of making your first dashboard.

Let’s get started!

Create  Dashboard in Power BI: Table of Contents

  • How to Create Dashboards in Power BI: Step-by-Step Guide
  • Augmented Tech Labs: Helping You Build Power BI Dashboards
  • Create Dashboard in Power BI: FAQs

How to Create Dashboards in Power BI: Step-by-Step Guide

Before we get started with the tutorial, there are 2 prerequisites you will need to follow along:

  • First, a Power BI Desktop Account (I’ve used the free version to create this tutorial). 
  • Second, a sample file, like an Excel sheet with at least a few rows and columns. 

Once you’ve got these ready, follow this simple Power BI Dashboard tutorial:

Step 1: Connect to Your Data Source

The first step in building dashboards in Power BI is to connect your data with the tool. To do this:

  1. Open Power BI Desktop.
  2. On the “Home” page, click on “Get Data” and choose the source of your data. For this tutorial, I recommend starting with Excel.
  3. Browse to and select your Excel file.
  4. The “Navigator” window will appear and tell you which sheets and tables are available in your workbook.
  5. Select the table(s) you want to use and click “Load” to import them directly.
  6. Alternatively, you can also click on “Transform Data” to clean and shape your data first.

Pro Tip: Using Transform Data opens the Power Query Editor, one of the most powerful data visualization tools for cleaning messy data before it even enters your model.

Step 2: Build Your Data Model (Table Relationships)

If you loaded multiple tables, you need to define how they connect. This is what we call “data modelling.”

And a proper data model is the engine behind effective Power BI Dashboards. Without it, Power BI will not be able to understand how different data points are connected internally.

Here’s how you can build your data model:

  1. On the left-hand pane, click the “Model” view (it should be the third icon from the left).
  2. Power BI may auto-detect and create relationships (this will appear as a line between tables).
  3. If Power BI does not auto-detect and create relationships, don’t worry. You can create one manually by clicking and dragging a field (e.g., CustomerID) from one table to the related field in another table.

Remember, properly defining relationships in this step is crucial. It will ensure that your filters and visuals work correctly across different tables.

Step 3: Create Your Report with Data Visualization Tools

This is the step towards which we have been building up, the step where you bring your data to life.

 

Here’s how you can build your dashboards in Power BI via the report visuals option:

  1. Go to the Report view (the first icon on the left pane).
  2. On the right, you should see the Fields pane (i.e., your data tables) and the Visualizations pane (i.e., charts and formatting options).
  3. To create a visual: Select a chart type from the Visualizations pane (e.g., a Stacked Bar Chart). Then, drag fields from the Fields pane and drop them into the Axis, Legend, and Values buckets well.
    For example, if you want to see “Sales by Region”, drag Region to Axis and Sales to Values.
  4. If you want to add more visuals to your dashboard, just repeat this process. Add different visuals like line charts, maps, or KPIs to your report canvas to tell a complete story. 

The report page that you have created in this step will become the source for your dashboard.

Step 4: Create Your Power BI Dashboard

As soon as you’re done with Step 3, you have created the basis for your Power BI dashboard. 

The next step in the process of building Power BI Dashboards is to bring your report to life.

  1. Save your .pbix file and then click Publish on the Home page. This is where you are publishing your report to the Power BI Online Service.
  2. Once published, your browser will open to the Power BI service. Open the published report.
  3. Once you are viewing the report, hover over any visual. Next, click the Pin icon (it’ll look like a pushpin) that appears.
  4. A dialog box will ask you to pin this visual to a new or existing dashboard. Select New dashboard, give it a name (e.g., “Sales Overview“), and click Pin.
  5. Repeat this process, pinning other key visuals from your report(s) to the same dashboard. 

You are now effectively creating a dashboard in Power BI by adding the most important metrics of your report onto a single canvas.

Step 5: Enhance and Customize Your Dashboard

Till now, we have created a canvas with several “pinned tiles”.

 

But a great dashboard is more than just pinned tiles! It uses the full power of data visualization tools to create a source for effective decision-making!

 Let me show you how to customize your Power BI dashboards: 

  1. On your dashboard, click Edit.
  2. Add Text Boxes or Images: You can use the “+ Add a tile” button to include labels, commentary, or company logos. This will give context to viewers or enhance the appeal of your dashboard.
  3. Resize and Arrange: You can also click and drag the corners of visuals to resize them. I highly recommend dragging tiles to arrange them in a logical, easy-to-follow layout.
  4. Apply a Theme: One of the best things about building dashboards in Power BI is that you can apply consistent color schemes throughout your visual for a professional look. To do this, click on Dashboard theme and select a color scheme that suits you.

Step 6: Share and Collaborate

This is the final step of this Power BI dashboard tutorial: sharing your work with colleagues and stakeholders. 

This is another strength that makes Power BI one of the best data visualization tools – it offers several robust collaboration options, such as:

1. Direct Sharing:

  • From your dashboard in the Power BI service, click the Share button (look for this at the top right of the screen).
  • Enter the email IDs of your colleagues or stakeholders. You can also add a message and configure whether recipients can reshare the dashboard or just view it.
  • Click Share, and they will receive an email notification with a direct link to the dashboard.

2. Publish to Web (Use with Caution!):

  • For broader, public sharing, select File > Embed report > Publish to web (public).

Remember, when you click on “Publish to Web,” it will create a link that anyone on the internet can see, even if they don’t have a Power BI license! So, I suggest using this only for non-sensitive data intended for a public audience!

3. Workspace Apps (For Enterprise Teams):

  • If your dashboard is saved within a workspace, you can publish it as an App.
  • To do this, navigate to your workspace and click on Create app.
  • You can then configure the audience, specific pages to include, and a custom theme before publishing the app for your entire organization or a specific group.

4. Microsoft Teams Integration:

  • Lastly, you can directly tab and share your dashboard or report within a Microsoft Teams channel for seamless collaboration.

Once you have shared your Power BI report with the relevant stakeholders, they can view the dashboard and interact with filters. Plus, if you have granted them permission to do so, they will also be able to see the underlying reports that you have used to make the dashboard. 

This will turn your Power BI Dashboard into a central hub for data-driven decision-making!

Step 7: Enhance Interactivity and Maintain Your Dashboard

Once you have published and shared your Power BI dashboard, it is technically live. However, the process of building dashboards in Power BI is often iterative. 

And one way to enhance your dashboard’s appeal over time is to increase its interactivity.

Here’s how you can do this:

  • Use Slicers and Filters: You can add timeline slicers, dropdown menus, or checkbox filters to allow viewers to explore the data on their own terms. It will add dynamism to your data.
  • Configure Drillthrough: Drillthrough pages are detailed pages that focus on a specific tem, for example, a region within the chart. Once you have set up a drillthrough, users can right-click on a data point and “drill through” to a detailed page focused on that item!
  • Leverage Tooltips: One of the best things about Power BI dashboards is that you can create rich, custom tooltips that appear when hovering over visuals. These will provide viewers with additional context and metrics while keeping the main view clean and concise.
  • Schedule Data Refresh: To ensure your dashboard remains accurate, I highly recommend configuring a scheduled refresh for your dataset in the Power BI Service. To do this: 
  1. Go to your Workspace.
  2. Navigate to the Datasets tab and select your dataset.
  3. Go to Settings and configure the refresh schedule under the Data Source Credentials and Scheduled Refresh sections.

And that’s it! You’ve successfully created and iterated your first Power BI dashboard!

Also Read: 10 Data Visualization Best Practices – How to Convert Data into Insights

Augmented Tech Labs: Helping You Build Power BI Dashboards

Through this complete, step-by-step tutorial, we have discussed the A to Z of how to create a Power BI dashboard from scratch. I have also outlined how you can deploy them as a powerful, interactive tool for your entire organization.

Now, it’s time for you to slowly and steadily start building your first dashboard using Power BI.

And if you get stuck at any step in the process, you can reach out to us at Augmented Tech Labs! We have been using data visualization tools like Power BI for over a decade to help solopreneurs, enterprises, and SMBs create interactive dashboards for their operations. 

So, connect with us, and will help you troubleshoot and solve any and all errors that you might face in creating Power BI dashboards!

Create Dashboard in Power BI: FAQs

1. What is the difference between a Power BI Report and a Dashboard?

A Report is a multi-page canvas for detailed analysis. Power BI Dashboards are single-page, consolidated views built by pinning visuals from one or more reports.

2. Can I use Power BI Desktop for free?

Yes, Power BI Desktop is a free application for creating reports and data models. Publishing to the online service for sharing may require a licensed account.

3. What are the best data visualization tools within Power BI?

Power BI includes built-in data visualization tools like bar/line charts, maps, and matrices. The best tool depends on your data story and audience.

4. What is the first step to create dashboards in Power BI?

The first step is connecting to a data source. This foundational step in building dashboards in Power BI loads your data for modeling and visualization.

5. Where can I find more advanced Power BI dashboard tutorials?

For advanced design and efficiency techniques, Augmented Tech Labs offers expert guidance beyond this introductory Power BI dashboard tutorial.

Categories
Blog Data Visualization

Top Data Visualization Tools 2025

Are you stuck in the endless trial-and-error loop of finding the right data visualization tool for your business?

With numerous options available on the market, each with numerous promises, it’s easy to feel overwhelmed and frustrated.

One wrong choice can leave you with a tool that is too basic, too complex, or just not the right one for your needs. 

The truth is, it does not have to be that hard. We’ll help simplify your search for the right data visualization tool!

Say goodbye to the relentless back-and-forth and discover the perfect tool with our curated list of the top data visualization tools for 2025.

Let’s get started. 

Top Data Visualization Tools 2025: Table of Contents

  • What are the Best Data Visualization Tools for 2025?
  • What are Data Visualization Tools?
  • Top 7 Data Visualization Tools for 2025
  • Quick Tips to Choose the Best Visualization Tools for 2025
  • The Future of Data

What are Data Visualization Tools?

Data visualization tools are software solutions that help you visualize your raw and messy data in a visual form. By using visualizations such as graphs, maps, dashboards, and other visual aids, you can make your data more organized and easier to understand.

The process of data visualization enables you to interpret your data in a more intuitive and accessible manner.

You might ask, aren’t spreadsheets and notes good enough? Aren’t they doing the job just fine?

So, why do you really need data visualization for business? 

Why Do You Need Data Visualization?

Remember the times when you used drawings and charts in exams to support your answers? Why do you think you did that? Sure, to get some extra marks, but what else?

Visuals, pictures and images always help people understand data more clearly and concisely. Data visualization for businesses serves a similar purpose. 

Spreadsheets and notes may do the same thing, but what else do you see there beyond rows and columns?

  • Can you identify the trends or spot inaccuracies? 
  • Does it give future insights into your data or your business?

In our experience, the answer to both these questions is “No!”

Data visualization lets you do that and more. The best data visualization tools let you:

  • Spot trends
  • Make data-driven decisions 
  • Simplify your complex data
  • Real-time monitoring
  • Increases your business efficiency 
  • Enhances communications and 
  • Takes your business to new heights

However, not all tools are the same. Some are versatile and easy to use, while others have a lighter learning curve.

To find the right tool for your business, shopping around to see which one best suits your needs is always a good idea. 

We’ve hand-picked a few of the top data visualization tools in the market for you.

Ready to shop and find the perfect one for your business? Let’s go through our list!

Top 7 Data Visualization Tools for 2025

Data visualization for business plays a bigger role in business strategies and planning than ever before. The global market for these data reporting tools is projected to reach $19.5 billion by 2031.

Now that we’re in 2025, we don’t want to miss out on the latest and upgraded visualization tools for our projects, and we know you won’t either.

So, let’s have a look at the 7 best data visualization tools for 2025.

Let’s dig in.

1. Power BI

G2 Rating: 4.5/5

Power BI is an interactive and user-friendly platform for data visualization. It is one of the top data reporting tools amongst businesses, especially embedded into the Microsoft Ecosystem.

The tool continues to be amongst the top favorites due to its integration with Excel, SharePoint, and Teams. Moreover, it functions with different datasets, including Teradata, Salesforce, and SQL Server. 

It offers eye-catching visuals and powerful insights, and quickly turns complex data into easy-to-comprehend visualizations.

What are the Features of Power BI?

  • Advanced predictive analytics with Microsoft Copilot
  • Custom visualization templates
  • Robust security for sensitive data

Pros of Power BI:

  • User-friendly and does not need much technical expertise.
  • Smooth integrations
  • Offers customizable dashboards
  • No speed or memory issues
  • Compatible with the Microsoft product range.

Cons of Power BI:

  • Limited to the Microsoft Ecosystem
  • Cannot handle many different datasets

Pricing:

  • Basic: Free
  • Pro: $10 per month per user
  • Premium: $20 per month per user
  • Embedded: Variable

How does Power BI Stand Out for 2025? 

Apart from being one of the best data visualization tools, Power BI is also one of the most cost-effective options. It stands out in terms of value and accessibility. Its integration with AI features and predictive analytics gives you the ability to gain deeper insights.  

2. Tableau

G2 Rating: 4.4/5

Tableau is number 2 in our list of top data visualization tools. It is used to build powerful dashboards for efficiency analysis.

Best for business intelligence, data storytelling and creative interactive dashboards, Tableau provides AI-driven functionality for visualizations. 

Tableau’s drag-and-drop features remain intuitive, and its features with AI-powered analytics have been significantly enhanced.

What are the Features of Tableau?

  • AI-driven insights through Natural language queries. 
  • Real-time data analytics with improved speed. 
  • Enhances mobile capabilities. 

Pros of Tableau:

  • Powerful visualizations
  • User-friendly interface
  • Mobile responsiveness
  • High performance 
  • Accessibility to many data sources 
  • Strong user community

Cons of Tableau:

  • Expensive on the pricing side
  • Lacks auto-refresh and report scheduling options

Pricing:

  • Basic: Free version
  • Advanced Functionalities: Available for $75 per user per month

How does Tableau Stand Out for 2025? 

It focuses on self-service analytics, empowering users with minimal technical expertise to create professional-grade visualizations. It also seamlessly integrates with cloud platforms like AWS and Azure.

3. Looker Studio

G2 Rating: 4.4/5

Looker Studio, now a part of Google Cloud, is another data visualization tool that offers advanced analytics and data exploration capabilities. 

Formerly known as Google Data Studio, Looker offers real-time analytics to help you track metrics like web traffic and performance. 

What are the Features of Looker Studio? 

  • Direct integration with Google Ads, Analytics, and BigQuery
  • Automated dashboard with real-time data 
  • Enhanced sharing and collaboration

 Pros of Looker Studio:

  • Seamless integration with Google Tools
  • User-friendly interface  
  • Strong collaboration options
  • Real-time analytics for digital marketing

 Cons of Looker Studio:

  • Limited customizations for non-Google datasets
  • Technical expertise is required for advanced features

 Pricing: 

  • Pay-as-you-go pricing model
  • They offer a pricing calculator tool to help you estimate costs based on your specific needs. 

How does Looker Studio Stand Out for 2025?

Looker Studio stands out due to its expandable features. With easy integration and actionable insights, it can be a promising option for the marketing and e-commerce industries. 

4. Qlik Sense

G2 Rating: 4.4/5

QlikSense is a self-service data visualization tool that features an AI-powered data analysis engine. Its AI-powered insights and predictive analytics let you mirror how the human mind processes information.

It offers a no-code environment for ML models and advanced analytics, making it easily accessible to users of all levels.

What are the Features of QlikSense? 

  • AI-powered, intuitive data recommendations
  • Real-time, interactive storytelling
  • Advanced multi-cloud development 
  • Robust security options

Pros of QlikSense:

  • Uses AI and machine learning for data analytics 
  • Automatic chart updates based on data content
  • Seamless integration with different data sources

Cons of QlikSense:

  • Steeper learning curve
  • It can be expensive for small enterprises

Pricing:

  • Free trial before upgrading 
  • Basic: $825 per month, with a starting price of 25 GB and 20 full users, billed annually. 
  • Premium: $2500 per month, with a starting price of 50 GM and 20 full users, billed annually. 

How does QlikSense Stand Out for 2025? 

It seamlessly connects unrelated datasets, and its advanced security measures make it a top choice for many. It differentiates itself with its unique associative data model, and the 2025 version pushes the envelope further. 

5. Cognos

G2 Rating: 4/5 

Cognos Analytics from IBM is another business intelligence platform. It is designed to completely support the analytics cycle, from data discovery to operationalizing insights. 

It caters to a variety of users and helps you transition quickly from simple to complex and advanced analytics.

What are the Features of Cognos? 

  • AI-powered insights with data discovery, predictive analytics and pattern recognition.
  • Customizable visualizations and dashboards.
  • Integrates seamlessly with a variety of data sources, including SQL Server, Oracle and cloud-based platforms. 
  • Offers multi-data source reporting and ETL functionalities. 

 Pros of Cognos:

  • AI-powered analysis
  • Clear and detailed reporting with customizable dashboards 
  • Wide data source compatibility 
  • Predictive and pattern recognition

 Cons of Cognos:

  • It may take some time for new users to adapt. 
  • Small teams might need technical support due to advanced and extensive features.

 Pricing: 

  • They offer flexible pricing options for individual users and enterprises.
  • Standard Cloud On-Demand Price: $10.60 per month per user. 
  • Premium Cloud On-Demand Price: $42.40 per month per user. 

How does Cognos Stand Out for 2025? 

It stands out for its AI-driven and comprehensive capabilities. It is ideal for enterprises with complex, high-volume data and offers security features, such as role-based access and single sign-on.

6. Infogram

G2 Rating: 4.7/5

Infogram is another easy-to-use but prominent web-based data visualization tool. It is focused on creating visually appealing designs, interactive infographics, reports, and charts with AI.

It caters to all users and offers an extensive library of millions of icons, GIFs and photos.

What are the Features of Infogram? 

  • Drag-and-drop interface for easy design 
  • Wide range of customizable templates, maps and charts
  • Real-time data embedding and integrations

Pros of Infogram:

  • User-friendly 
  • Visually appealing content 
  • Customizable elements: Colors, styles etc. 
  • Facilities shareable content creation with built-in metrics for tracking engagement

Cons of Infogram:

  • Limited functionalities in the free version 
  • Less advanced compared to some competitors
  • Users may struggle with integrating custom fonts and datasets

Pricing:

  • Basic: Free
  • Pro: $19 per month, billed annually 
  • Business: $67 per month, billed annually
  • Team: $149 per month, billed annually
  • Enterprise: Contact their team for more information.

They also offer discount prices during specific festival sales. 

How does Infogram Stand Out in 2025? 

The data remains fresh by constantly updating its visualizations, which helps with real-time insights and quick decision-making. 

7. Domo

G2 Rating: 4.3/5

 

Domo is a cloud-based interactive data visualization tool that allows you to create real-time interactive visualizations in the form of more than 150 charts.

It’s a data visualization and business intelligence tool designed to connect, visualize, and analyze data from multiple sources. Major organizations, such as Cisco and Emerson, use Domo.

What are the Features of Domo? 

  • Real-time data connectivity and integration
  • Interactive dashboard 
  • Drag-and-drop functionality
  • AI-driven insights 
  • Automated alerts

Pros of Domo:

  • A wide array of reports and chart templates
  • Can analyze data from over 1,000 sources
  • Strong mobile capabilities for on-the-go access
  • Real-time collaboration and decision-making

Cons of Domo:

  • Pricing can be a bit expensive for smaller businesses
  • Steeper learning curve for advanced features

Pricing:

Domo offers a free 30-day trial. Pricing options are tailored to every organization’s unique needs. Contact their support team for the best pricing options. 

How Domo Stands Out for 2025? 

Its real-time data and user-friendly dashboards help you make informed decisions in a timely manner. 

Quick Tips to Choose the Best Visualization Tool for 2025

Overwhelmed by choices? Which of the 7 is the best interactive data visualization tool for you? How do you choose the one that best fits your business needs? 

 

What do you need? A tool with a user-friendly interface or customizable options? To find a tool, start by asking yourself a few questions. Some of these questions could include:

  • What are your visualization goals? 
  • What is the complexity of your data? 
  • Do you have large datasets? 
  • Do you need a tool that integrates with your existing CRM or ERP software?
  • What is your budget? 
  • What features do you need? 
  • Do you need tools that support cross-functional platforms or AI-driven insights?
  • Do you need a tool that scales with your business?

Answering these questions can help you narrow down your options for data reporting tools. Once that is done, you can gain a clearer picture of which data visualization tools align with your budget, needs, and 2025 business goals. 

The Future of Data

Interactive data visualization tools are changing the future of data. These tools are not just making data look prettier, but also changing how we understand and share it.

Moreover, with AI and machine learning transforming the technological landscape, it’s exciting to imagine what will come next.

If you’re still not sure which data visualization tool you should choose, we at Augmented Systems can help!

Our team of experts is always up to the minute with the latest technologies and ready to assist you in choosing the best data visualization for your needs!

Connect with us to find out which data visualization tool is ideal for your enterprise operations!

Top Data Visualization Tools 2025 FAQs:

1. What is the future of data visualization?

The future of data visualization is very promising with new technologies and trends, including:

  • AI-Driven Insights
  • Real-time Visualization
  • AR( Augmented Reality) and VR (Virtual Reality)
  • Improved Data Storytelling
  • User-Centric Designs

2. How to read a bar chart?

To read a bar chart: 

  1. Check the Axes: The x-axis shows categories or periods, while the y-axis indicates values.
  2. Compare Bar Heights/Lengths: Taller or longer bars represent larger values.
  3. Look for Patterns: Identify trends, differences, or clusters across the bars.
  4. Read Labels: Ensure you understand the units and categories being compared.

Bar charts make comparing data across different groups or time intervals easy.

3. Which data visualization method works best to show trends over time?

A line chart is the most effective way to show trends over time. It clearly displays data points connected along a continuous timeline, making identifying patterns, peaks, and declines easy. 

4. What are the two main uses for data visualization?

The two main uses for data visualization are: 

  • Simplifying complex data sets into simple and easy-to-understand visuals.
  • Help make data-driven decisions.

5. Is SQL a visualization tool?

 

Structured Query Language (SQL) is a widely used programming language for interacting with relational data in areas like business analytics. Professionals commonly use SQL for tasks such as data manipulation, analysis, and visualization.

Categories
Blog Data Visualization

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

Many companies, including 97% of Fortune 500, rely on Power BI for data-driven decision-making.

However, with so many features available, identifying the most useful feature can be challenging.

As a data visualization consultant, I understand how overwhelming it can be to choose the right features. Trust me, even I spent a lot of time trying out different features before I got the hang of it!

Staying informed about these features can help you maximize Power BI’s potential in your work. That’s why, to make things easier, I’ve put together a list of the top 9 features of Power BI you should know to make the most of it. 

But before we dive in, let’s first understand what Power BI is. 

Features of Power BI: Table of Contents

  • What are the Top 9 Features of Power BI for 2025?
  • What is Power BI?
  • What are Power BI’s 9 Best Features For Better Business Decisions?
  • Turn Your Data into Decision With Power BI + Augmented
  • Features of Power BI: FAQs

What is Power BI?

Microsoft Power BI is a powerful business intelligence tool to help you simplify data analytics and reporting. It lets you and your teams collaborate, visualize insights, and make data-driven decisions in real-time.

Power BI seamlessly integrates with hundreds of data sources, including:  

  • Excel spreadsheets,
  • On-premise SQL servers
  • Cloud-based databases 
  • And more!

With Power BI, you can transform complex datasets into clear, easy-to-understand visuals and reports. 

The best part? You don’t need any advanced technical skills. Its user-friendly interface allows you to create compelling visualizations that make data easier to understand.

However, without following best practices or consulting the right data visualization consultants, you may run into common challenges that can affect data accuracy and insights. 

That’s why understanding Power BI’s key features is important. 

 

These features help you make the most of its capabilities while helping you avoid common mistakes. 

In the next section, we’ll explore the top Power BI features that can enhance your data analytics experience. 

What are Power BI’s 9 Best Features For Better Business Decisions?

There are many powerful benefits of Power BI that can help you analyze your data more efficiently and make smarter business decisions. 

 

In this section, I’ll walk you through the top features of Power BI and explain how each one can enhance your data visualization and reporting capabilities

 

Take a moment to explore these features and see which ones best fit your business needs. 

1. Extract Insights from Large Datasets

Handling large datasets can be challenging, especially if you are using traditional tools like Excel. 

Did you know Excel limits each worksheet to 1,048,576 rows?

 

While that might seem a lot, it can be restrictive if you need to work with massive amounts of data. 

 

Power BI eliminates these limits, offering a powerful and efficient way to handle large data sets. 

How Does Power BI Help Extract Insights With Large Datasets? 

  • Handles over 100 million rows using advanced storage technology
  • Optimizes performance with dedicated Cloud support 
  • Power BI’s in-memory storage and DirectQuery feature allow you to analyze vast datasets without long processing times
  • Connects seamlessly with multiple sources, like Excel, SQL and more, for a unified view
  • The interactive feature makes it easy to create dynamic reports and dashboards

So, if you are a business handling extensive data, Power BI is a great choice. It offers a scalable, high-performance solution that helps you extract insights without the constraints of a traditional tool. 

2. Create Custom Visualizations with R and Python

Power BI offers a range of built-in data visualizations, such as bars, charts, line graphs and more.

 

While these standard options cover most of your reporting needs, sometimes you need something more tailored to your specific analysis.

 

Custom visualizations with R and Python fulfill those custom needs. You can integrate Power BI with open-source libraries from R and Python and create highly customized visuals that go beyond the default options. 

How Does Custom Visualization with R and Python Help You?

  • You get more control over your visuals
  • Create advanced visuals with tools like ggplot2 (in R) and Matplotlib (in Python)
  • Add predictive models, trend lines, and statical insights directly into your dashboards
  • Easily embed R and Python scripts into Power BI without complex setup
  • Clear, customized visuals help you spot trends and insights faster

With that, Power BI gives you more freedom to explore your data your way so that you can create reports and dashboards that truly make an impact. 

 

3. Automatic Data Refreshes

If you are still making decisions based on your wild guesses and outdated data, you need to think again. Your data may not be up-to-date. Outdated data may lead to missed opportunities, reporting errors, and inefficiencies. 

With Power BI’s auto-refresh feature, you can trust that your reports and dashboards are always current and updated with the latest information in real-time. (Without manual efforts)

How to Create Your Data Up-to-Date With Automatic Refresh in Power BI?

 

  • Your data updates automatically, making sure you always work with the latest data
  • Saves time by eliminating the need to refresh reports manually
  • Reduces the risk of making decisions based on old and incorrect data
  • Seamlessly connects to multiple data sources, including Cloud services and databases
  • You can set up refresh intervals that match your business needs, like hourly updates or daily refreshes 

With this feature, you can make sure that your reports are always accurate, up-to-date and ready to support your business decisions without any extra effort!

 

4. Create Understandable Charts from Complicated Data

Did you ever struggle to make sense of endless spreadsheets packed with thousands of numbers? 

Power BI helps overcome this struggle by turning all your data into clear, easy-to-understand visual insights in just a few minutes

 

So, even if you are not a data expert, you can understand your data with just a glance without scanning through endless rows. 

How Power BI Helps You Visualize Your Data Effectively?

 

  • Turns numbers into meaningful visualizations, like bar charts, pie charts, and more
  • Offers a variety of built-in visualization options to present data in the best way possible
  • With interactive dashboards, it lets you click, filter, and explore data in real-time
  • Its dashboards are simple enough for anyone to understand
  • Lets you create custom visuals using R and Python, giving you complete control over how you want to display your data

Having data is one thing, but understanding it correctly is what makes a big difference. Power BI helps you do just that with just a few clicks

 

5. Reuse Datasets Among Different Reports and Dashboards

One of the most common mistakes in data visualization is working with inconsistent or duplicate datasets across multiple reports. 

Manually updating your numbers in different reports is a challenge

 

But that’s not the case with Power BI. It allows you to reuse datasets across various reports, ensuring consistency. That means you won’t have to manually update multiple versions of the same data in different reports. 

How Does Power BI Help Maintain Data Consistency?

 

  • Helps you create a single dataset containing KPIs, like gross profit, sales revenue, and customer retention rate, to use across multiple dashboards 
  • Eliminates redundant data processing to centralize data models and reduce errors 
  • Syncs all the reports into one single and trusted dataset to keep everyone on the same page
  • Reduces processing time and enhances report performance with shared datasets
  • The dataset-sharing feature helps standardize calculations and maintains accuracy across all reports

Maintaining a single source of truth for your data is the key to making informed business decisions. Power BI does just that and lets you focus on insights rather than fixing errors. 

 

6. Integration with Other Microsoft Products

One of Power BI’s biggest strengths is its ability to seamlessly integrate with Microsoft tools like Teams, PowerPoint, and Word. 

 

This feature makes it easier for you to collaborate, present insights, and streamline workflows without really having to switch between platforms. 

How Does Power BI’s Integration with Other Microsoft Products Help You?

 

  • Find and share Power BI reports directly in teams to keep everyone in the loop
  • You can export reports to PowerPoint and embed them into interactive presentations
  • Integrate Word Documents into Power BI to add report explanations and references in one place

Thus, by leveraging the benefits of Power BI’s integrations, you can simplify collaboration, enhance your reporting capabilities and improve your productivity.  

Pro Tip: If you need expert guidance on maximizing these integrations, consider our data visualization consulting services. We’ll help you make the most of your data!

7. Regular Updates

Microsoft’s commitment to continuous improvement is Power BI’s one of the biggest advantages and features. 

It receives frequent updates and ensures that you always have access to the latest features and enhancements. 

How Can You Stay Ahead With Power BI’s Regular Updates Feature?

 

  • Based on user feedback, Microsoft regularly updates and introduces new features
  • Each new feature improves speed, user experience and overall functionality
  • New and improved visuals help you present insights more clearly
  • Regular updates also include security enhancements, protecting your sensitive business data
  • Updates often include integrating compatibility with other Microsoft tools and third-party applications

If you are looking to stay ahead of the market trends, Power BI is your best bet, with up-to-date features every now and then.

 

8. Create Beautiful Maps

When you are dealing with location-based data, numbers alone won’t tell you a complete story. 

 

Power BI’s mapping features make your insights clearer and more actionable. That means you won’t have to scan through rows of data. Instead, you can visualize trends, patterns, and relationships on a map easily. 

How Power BI’s Beautiful Maps Help You With Better Business Decisions?

 

  • Offers multiple map types, such as Standard Maps, Filled Maps, ArcGIS Maps and more
  • Get interactive features, like zoom in and drill down for deeper geographical insights
  • Perfect for you if you are analyzing sales territories, tracking deliveries or understanding customer locations
  • Integrates with Bing Maps and GIS data sources for accurate location-based insights

Power BI lets you understand the map’s effectiveness so that you can make better and faster decisions.

 

9. Enhancing Reports with Advanced Power BI Features

Power BI goes beyond basic reporting as it provides advanced features that help you analyze, customize and secure your data more powerfully. 

How Can You Take Your Power BI Reports to the Next Level?

 

  • Publishing as Apps

– Share reports with different audiences using a single link
– Simplifies report distribution for large teams
– Each user can see a customized version of the data

  • Report Themes

– Maintain a consistent look and feel across all your reports
– Customize reports to match your brand
– Save time by applying pre-set color schemes and layouts

  • Row-Level Security (RLS)

– Control who sees what within your report
– Assign security roles to ensure users access only relevant information
– Enhances data confidentiality and management across different teams and departments.

Using these advanced Power BI features, you can enhance your data presentation, improve the security of your data and streamline report sharing

Turn Your Data into Decision With Power BI + Augmented

What would happen if you could make every business decision in real-time and with accurate insights?

  • Real-time data updates for accurate insights
  • AI-powered analytics to uncover trends instantly
  • Intuitive dashboards for a clear data overview
  • Seamless automation for effortless reporting

The answer is simple: Smarter, faster, and more confident business decisions. 

That’s exactly what you can get with Power BI and Augmented

Features of Power BI: FAQs

1. Which Power BI feature is the most helpful?

Although each feature offers a distinct value proposition, the most compelling reason to choose one is the ability to extract significant insights effectively from huge datasets.

2. What data visualization tool features does Power BI offer?

Power BI excels as a data visualization tool. It allows users to convert their data into interactive visuals, such as graphs and charts, to facilitate understanding and decision-making. 

Some of the salient features of Power BI are:

  • Extract Insights from Large Datasets 
  • Create Custom Visualizations with R and Python
  • Automatic Data Refreshes
  • Create Beautiful Maps
  • Monthly Product Updates

3. How does Power BI ensure data security?

Power BI implements efficient data security features, including row-level security and dynamic data masking, to protect sensitive information. By maintaining governance and confidentiality, administrators can control data access and ensure users only view authorized information.

Categories
Blog Data Visualization

Power BI vs Tableau: Which is the Better Data Visualization Tool

Confused between two business intelligence tools – Power BI and Tableau?

You have come to the perfect blog!

I have used both data visualization software for a lot of different data analysis projects.

The good news is that you’re stuck between two of the best data visualization tools on the market.

Sure, both Power BI and Tableau share considerable overlap in their features. But they also have a lot of major differences.

Not to worry: in this guide, I am going to help you decide which tool is perfect for your use case.

To do this, we will discuss their similarities, differences, and ideal use cases. 

  

If you are in a hurry, check out the quick table of differences – I have summarised my findings to help you quickly choose the right software. 

Tableau vs Power BI: Table of Contents

  • Quick Table of Comparison: Power BI vs Tableau
  • What is Power BI?
  • What is Tableau?
  • Power BI vs Tableau: What are the Key Differences?
  • Which is the Best Data Visualization Software: Power BI or Tableau?
  • Tableau vs Power BI: FAQs

Quick Table of Comparison: Power BI vs Tableau

Short on time?

I’ve got you covered! Check out this quick table of comparison to find out which tool is right for you:

Feature

Power BI

Tableau

Best For

Beginners, Microsoft shops, budget-conscious teams

Data experts, large enterprises, complex visualization

Cost

$9.99/user/month (Pro)

$70/user/month (Creator)

Visualization

Quick, standard reports

Advanced, highly customizable dashboards

Data Handling

Good for typical business data

Excellent for large, complex datasets

Integration

Excellent with Microsoft products

Wide range (Python, R, Salesforce, Slack)

Programming

DAX, M, R

Python, R, Java, C++ via SDK

What is Power BI?

Power BI is Microsoft’s native business intelligence software.

 

Naturally, this means it has deep integration with all other Microsoft products:

  • Excel 
  • Azure
  • SQL

So, if your organization already uses Microsoft products, choosing Power BI can be very beneficial.

You will have to spend very little time on data prep and cleaning: it can be as simple as a plug-and-play system for data analysis.

But its deep integration is not its only strength!

Power BI is also known for its:

  • User-friendly interface.
  • Affordability.
  • Extensive data connectors.

 

So, despite being a relatively new data visualization tool, Power BI is one of the best Tableau competitors on the market!

Power BI Features

  • Comes with a wide range of options you can use to visualize data. 
  • Lets you define and create a wide range of relationships between different rows and columns. 
  • Offers a very good mobile experience: you can create and share reports + dashboards on the go. 
  • Supports real-time data refreshes for live dashboards. 

 

Also Read: Data Visualization Best Practices in Power BI

Power BI: Pros and Cons

Benefits

Drawbacks

Simple UI that facilitates collaboration + report sharing.

Creating complex relationships between data can be challenging.

Supports highly detailed interactive dashboards.

The free version offers very limited functionalities.

You can add or connect data from a lot of different sources.

What is Tableau?

Tableau is a data analysis and visualization tool that debuted in 2003. It was then acquired by Salesforce back in 2019.

Since then, it has become a part of the powerful Salesforce stack.

Today, it is one of the most popular business intelligence (BI) tools on the market.

Why? Primarily because you can choose from a very wide range of visualizations:

  • Gantt Charts
  • Heat Maps
  • Scatter Plots
  • Treemaps

But what I really like about Tableau is that it can handle large datasets very easily.

Plus, you can import data from multiple sources and get AI-powered insights whenever you need!

Let us go through some of its standout features.

Tableau Features Comparison

  • Comes with native tools that help you clean, transform, and organize data before analysis.
  • You can easily share and integrate Tableau with tools like Slack and Salesforce.
  • Lets you create visualizations by simply feeding in text queries like, “Analyze last quarter’s sales performance”.
  • It can handle large datasets and complex queries, so you can scale without worrying about hitting a ceiling. 

Tableau: Pros and Cons

Benefits

Drawbacks

Has a powerful mobile application.

Some configurations are very complex: you will need either a highly skilled IT team or expertise to properly use them.

Handles large datasets with ease.

Expensive subscriptions, which make it an enterprise-grade tool. 

The centralized data repository is very convenient for storing and retrieving data.

Tableau vs Power BI: What are the Key Differences?

In this section, I have compared Tableau and Power BI based on five key features:

  • Data Visualization
  • Cost
  • Security 
  • Dashboard Features
  • Programming Language

So, if you are in a hurry, just jump to the feature most relevant to you!

1. Data Visualization

First, let’s compare their primary function: how well can each of these tools visualize data and information?

Data Visualization Feature

Tableau

Power BI

Primary Strength

Advanced, highly interactive, and customized dashboards.

Strong, user-friendly features for quick report creation.

Ease of Use

Steeper learning curve.

Easier for beginners.

Key Advantage

Superior customization and interactivity.

Speed of development & excellent integration with the Microsoft ecosystem (e.g., Excel).

Target User

Users who need deep, granular control over visual design.

Beginners and users who need to create reports quickly.

Key Takeaway

I recommend Tableau if you want to create & define complex relationships between your data using innovative visualization options.

But if what you need is a tool that supports speed over complexity, go for Power BI!

2. Tableau vs Power BI Cost

When it comes to cost, Power BI is the clear winner.

It is a budget-friendly data visualization software: its basic plan costs very little compared to Tableau’s basic plan.

But that’s by design: Power BI is a tool built for small businesses and startups. Tableau, on the other hand, is an enterprise-grade tool.

Feature

Power BI

Tableau

Overall Cost Impression

Budget-friendly

Significantly more expensive

Starting Price

 

$9.99/user/month

$70/user/month

Cost Comparison

The basic Pro plan is 7 times cheaper than Tableau’s Creator plan.

The Creator plan is 10 times more expensive than Power BI’s basic Pro plan.

Key Takeaway

If cost is your deciding factor, go for Power BI.

However, if you are a data analyst or need an enterprise-grade tool that can handle large datasets, Tableau will be worth paying $70/month!  

3. Security Features

Next, let us compare the two tools based on a non-negotiable, all-important feature: security.

Feature

Power BI

Tableau

Overall Approach

Pre-built, enterprise-grade security. Integrated with Microsoft Azure.

Highly configurable. You can tailor the security settings.

Data Storage

Uses Azure BLOB storage and Azure SQL.

Based on your own infrastructure and needs.

Authentication & Access Control

Uses the Azure Active Directory (AAD).

Provides pre-set user roles (Viewer, Interactor, Editor). You can then add custom roles with tailored abilities.

Data-Level Security

Row-Level Security (RLS).

Row-Level Security (RLS) + you can restrict access based on roles.

Network Security

Employs TLS encryption for data in transit.

Recommends SSL and HTTPS configurations for secure communications.

Key Takeaway

Power BI’s security features are strongly tied to its Azure framework. So, your data will remain secure. But, it offers very little customization, so you can’t customise the settings outside the Azure infrastructure.

On the other hand, Tableau offers flexibility, putting you in-charge of configuring user roles and restrictions. 

4. Dashboard Features

Next, let us compare how the two platforms help us make and share business intelligence dashboards:

Feature

Power BI

Tableau

UI and Usability

Intuitive and user-friendly.

Steeper learning curve.

Interface & Creation

Simple drag-and-drop functionality, perfect for creating dashboards quickly.

Highly customizable, let you create detailed and rich designs.

Core Strength

Speed.  

Complexity. 

Interactivity

Interactive visuals that update in real-time.

Interactive filtering, drill-down, and real-time updates. Lacks data refreshes.

Key Takeaway

If you’re a beginner, start with Power BI. The drag-and-drop dashboard builder will be perfect for you.

However, if you need rich, in-depth visualization capabilities, Tableau is the better option!

5. Programming Language

I’ve included this last point exclusively for technical users and data analysts out there.

Here, I have briefly compared the programming languages that both the tools offer:

Feature

Power BI

Tableau

Primary Languages

DAX (Data Analysis Expressions) for modeling.

M Language for data manipulation.

No primary built-in language, but offers extensive external integrations.

Advanced Analytics

Supports R programming for statistical analysis.

Integrates with R and Python for statistical computing and analysis.

Extensibility & SDK

External integrations are somewhat limited.

Offers SDK for integration with Python, Java, C, and C++.

Overall Flexibility

Powerful within its own environment, but less open.

High flexibility and a wider range of integration options.

Key Takeaway

If you want to use Power BI, you will have to master DAX. So, only use Power BI if you don’t have any other option but to use a tool that integrates very well with Microsoft products.

However, if you need flexibility and don’t want to spend time learning DAX, Tableau is the clear winner. 

Power BI or Tableau? Final Verdict

Through this blog, we have seen that both Power BI and Tableau have their own strengths and weaknesses. Both of them:

  • Cater to different users.
  • Offer different security features.
  • Use different programming languages for advanced analysis.

 

So, which one should you choose?

My verdict:

If you are a Microsoft user or comfortable with learning a new language for complex analysis, go for Power BI. I also recommend Power BI if you’re a beginner or need a budget-friendly tool.

If you need a tool that helps you visualize complex relationships, go for Tableau. It will give you the flexibility, security, and advanced visualization capabilities.

And if you have a very specific use case for which you need a data analysis and visualization tool, why not get in touch with us at Augmented Tech Labs?

Our experts will understand your requirements and suggest a tool that will help you achieve your immediate goals without compromising your ability to scale your data visualization needs!

Power BI vs Tableau: Frequently Asked Questions

1. Which is superior, Tableau or Power BI?

Tableau is the better option if you need a tool that lets you tell attractive visual stories with your data. However, Power BI is definitely the better choice if you need a platform that integrates well with Microsoft products and is easy to use.

2. Should I study Tableau or Power BI?

I suggest starting with Power BI if you are just starting out with data visualization. It was much easier to use for simple operations when I started out, and it’s still the case today!

3. Is coding necessary for Tableau?

No, coding is not necessary for Tableau. However, if you know a little bit of languages like Java, it will give you more options to create visualizations and analyze data.

Categories
Blog Data Migration

8 Best Data Migration Tools for Moving Data in 2025

The post-COVID-19 era has shifted the role of data in digital transformation, bringing exponential growth in data collection.

But with more data comes more challenges, especially when it comes to migrating it to different platforms.

Transferring large amounts of data isn’t as simple as copying and pasting files. It can be messy, complicated, and even risky! In fact, many organizations face difficulties in migrating vast amounts of data securely.

And let’s be honest, no one wants to deal with the headache of missing or corrupt data

 

But here’s the good news: Data migration tools can simplify this daunting task and make your migration process much easier. 

 

These tools facilitate data transfer by simply selecting, preparing, and extracting data from one storage to another.

 

As a seasoned Data Migration Consultant, I’ve compiled a list of 8 game-changing tools that can help you transfer your data safely and efficiently

 

In this article, I’ll cover:

  • The 8 Best Data Migration Tools
  • Their Pros & Features
  • User reviews
  • The Role of a Data Migration Consultant

Let’s go!

8 Best Data Migration Tools 2025: Table of Contents

  • What are the 8 Best Data Migration Tools for Moving Data in 2025?
  • What are the Best Data Migration Tools? 
  • What Should You Hire a Data Migration Consultant?
  • Master the Art of Data Transfer with Data Migration Services
  • 8 Best Data Migration Tools 2025: Frequently Asked Questions

What are the Best Data Migration Tools? 

Data migration isn’t something you want to leave to chance or luck. One wrong move, and you risk losing all your valuable data. 

But it doesn’t have to be that way!

Data migration is not just about moving your data; it’s about transferring it quickly, securely and without disruptions. And the right tools can make all the difference.

After testing multiple tools, I’ve seen firsthand how the right choice can save time, reduce errors, and make the entire migration stress-free.

So, which tool actually works the best?

In this section, I’ve selected the best data migration solutions that make the process simple, scalable and straightforward.

Let’s break down the 8 best data migration services one by one.

1. AWS Data Migration Services

G2 Rating: 4.1/5 stars (51 reviews)

AWS Database Migration services are the #1 solution for homogeneous and heterogeneous database migrations, making them a go-to solution whether you’re keeping the same database type or switching to a new one.

One thing I personally appreciate is that it allows you to automate the conversion of source databases into AWS-compatible formats. That means less manual effort, fewer errors, and a smoother migration experience.

One of the best things about AWS DMS is its free plan, which offers 2160 hours of usage over 90 days.

 

Thus, you can initially use AWS’s services without incurring any cost.

 

However, once the free plan is over, charges may apply based on specific requirements, as given in the pricing table below.

 

Timeline

Price

Cost during the initial 90 days

Free

Cost per hour

$0.042 per server

Cost per month

$30 per server

What are the Key Features of AWS DMS? 

  1. Continuous Replication: Ongoing replication for disaster recovery and consolidation.
  2. Wide Support: Compatible with major commercial and open-source databases.
  3. Schema Conversion: Automates schema and code conversion for migrations.

What are the Pros of AWS DMS?

  1. Supports a diverse database platform.
  2. Ensures a secure data transfer with robust encryption.
  3. It can easily integrate with other AWS services. 

If you are already using AWS or planning to migrate to the cloud, AWS DMS is a great choice. Its free trial, automation features, and wide database storage make it one of the best solutions.

Plus, it is a well-rated tool that balances performance, security, and affordability, which makes it worthwhile considering.

2. Fivertran

G2 Rating: 4.2/5 (406 reviews)

Fivertran stands out for its automation capabilities and minimal maintenance requirements when it comes to top data migration tools.

You can rely on it to sync your data from multiple sources into one centralized system without the need for code.

One thing I really liked about Fivertran is its quick setup. It doesn’t require complex configurations, making it easy to get started.

Plus, its maintenance-free operation reduces manual effort, so you can focus on data analysis rather than troubleshooting your transfers. 

Fivertran’s no-code, experience-led data transfer is the reason it’s the second-highest-rated tool on my list. Plus, the Fivertran pricing model lets you pay for what you use. 

It has 4 pricing plans, as shown in the image below.

What are the Key Features of Fivertran?

  1. Connector Library: Offers pre-built connectors for popular data sources and SaaS.
  2. Real-time Monitoring: Sends alerts about pipeline status and issues.
  3. Incremental Updates: Syncs only changed data, minimizing transfer costs.

What are the Pros of Fivertran?

  1. Offers an automated, real-time data replication.
  2. It supports a wide range of data sources and warehouses
  3. Its maintenance-free operation minimizes manual efforts.

Fivertran is a well-regarded enterprise data migration tool known for its automation and ease of use. So whether you are migrating to a cloud warehouse or consolidating multiple data sources, it’s a reliable solution worth considering!

3. Matillion

G2 Rating: 4.4/5 (80 reviews)

Matillion ETL is cloud-native data integration software you’ll want to check out if you’re working with modern cloud environments, such as Snowflake and Amazon RedShift.

It’s designed to make data migration and transformation faster, easier, and more efficient. 

 

One thing that really stands out about Matillion is its user-friendly interface. Even if you are not an ETL expert, you can design workflows with ease. 

It also comes with an extensive library of pre-built connectors, allowing you to pull data from multiple sources without extra coding. 

  

With its high-performance processing and cloud-native architecture, Matillion earns the #3 spot on my list of ETL tools.

 

Additionally, Matillion offers three pricing brackets to help users with diverse needs find the right fit.

 

Refer to the table below for more detailed information on pricing options.

 

Plan

Price

Developer (for individuals)

$1,000

Basic (for growing teams

$2,000

Advanced (for scaling business)

Request Pricing

What are the Key Features of Matillion?

  1. Pushdown Optimization: Uses cloud data warehouse processing for better performance.
  2. Comprehensive Connector Library: Offers a wide range of pre-built connectors for data sources and destinations.
  3. Data Quality Tools: Built-in features for maintaining data integrity and compliance.

What are the Pros of Matillion?

  1. It is designed for cloud database migrations.
  2. It has an efficient ETL capability for data transformation.
  3. A user-friendly interface for streamlined operations.

If your business relies on cloud-based data warehouses and needs a powerful yet easy-to-use tool, I strongly suggest exploring Matillion! 

4. Stitch Data

G2 Rating: 4.4/5 (68 reviews)

Stitch Data is a cloud-based ETL platform that easily moves data from point A to point B.

 

The tool is worth considering if you are looking for a no-code, straightforward tool for seamless data movement.

One of Stitch’s biggest advantages is its extensive connectivity. With 140+ supported data sources, you can effortlessly consolidate data from multiple platforms into a single destination.

So, whether you’re a small business or a growing enterprise, Stitch scales with your needs, making it a versatile tool for everyone.

Plus, with its automation-driven approach and easy integration, Stitch earns the #4 spot on my list.

 

Stitch has three pricing plans, thus making it affordable for different business needs.

 

Plan

Price

Standard Plan

$100

Advanced Plan

$1250/month

Premium Plan

$2500/month

What are the Key Features of Stitch Data?

  1. Singer Integration: Supports open-source Singer for scripting uncommon data sources.
  2. Automatic Schema Detection: Adapts to changes in source structures, thus reducing maintenance needs.
  3. Usage-Based Pricing: Transparent pricing model scales with data volume, accessible for all businesses.

What are the Pros of Stitch Data?

  1. Automates ETL, freeing businesses to focus on data analysis.
  2. Integrates data from over 130 sources for comprehensive consolidation.
  3. Scales with business needs, suitable for any organization size.

Stitch Data is a fantastic tool if your priorities are simplicity, scalability, and automation. 

5. MuleSoft

G2 Rating: 4.5/5 (688 reviews)

 

MuleSoft offers a unique data migration approach, focusing on API-led connectivity, earning it the 5th spot on my list.

 

Instead of just moving your data, it connects applications and systems effortlessly, ensuring a smooth and secure data flow across platforms. 

 

Moreover, MuleSoft simplifies the process with its powerful automation and pre-built connectors. This makes it an excellent choice for large-scale data migrations where connectivity and security are the key. 

 

Despite its salient features, the exact pricing of this tool is unavailable. However, you can connect with their team for customized quotes based on your specific needs. 

 

What are the Key Features of MuleSoft?

  1. Anypoint Studio: An IDE for creating, evaluating, and implementing integrations and APIs.
  2. DataWeave: A language for data transformation that makes format mapping simple.
  3. Pre-built Connections: More than 200 connections are available for widely used applications to expedite integration.

What are the Pros of MuleSoft?

  1. It offers API-led connectivity for seamless integration.
  2. A good option for cloud-based data migration projects.
  3. Facilitates the flow of data between different systems.

From what I’ve seen, users have praised MuleSoft for its reliability, scalability, and API-driven data migration solutions.

6. Integrate.io

G2 Rating: 4.3/5 (199 reviews)

Integrate.io is a cloud-based data transfer solution that enables seamless data transfer from various sources. It stands out for its simplicity and flexibility.

 

What makes Integrate.io unique?

Its intuitive drag-and-drop, no-code interface!

So, whether you are a data expert or a beginner, you can effortlessly connect over 140 databases, data warehouses and cloud data sources.

With its no maintenance operations, Integrate.io offers a hassle-free data integration experience. That’s why it earned the #6 spot on my top data migration tools list. 

What are the Key Features of Integrate.io?

  1. Transformations: Offers 220+ pre-built data transformations for easy mapping and structure automation.
  2. Encryption: Secures streaming data with field-level encryption during migration.
  3. Customer Support: Provides 24/7 support, including video calls, for immediate issue resolution.

What are the Pros of Integrate.io?

  1. Streamlines the integration and movement of cloud data.
  2. A platform that is straightforward to use for managing data.
  3. Facilitates the integration of data from multiple sources.

While the pricing details for Integrate.io are not publicly available on the website, its features make it a compelling choice for businesses!

7. Airbyte

G2 Rating: 4.5/5 (49 reviews)

Airbyte is an open-source data integration and migration tool that enables you to build custom connectors to tackle long-tail integrations.

 

Its API-first architecture promotes transparency and collaboration, making it #7 on my list of best data migration tools.

 

With Airbyte, you can easily connect to diverse data sources, benefiting from its huge library of 550 pre-built connectors. This flexibility allows you to manage both structured and unstructured data.

 

Airbyte provides cloud and self-hosted deployment options, offering you greater control over your data. Additionally, the platform needs no maintenance and automatically handles updates to ensure a seamless experience for all users.

 

For detailed information about pricing plans, kindly refer to the table below.

 

What are the Key Features of Airbyte?

  1. No-Code Configuration: User-friendly interface for managing data pipelines without coding.
  2. Data Normalization: Optional post-load normalization for consistent downstream analytics.
  3. Flexible Deployment: Supports cloud and self-hosted options for data control and infrastructure.

What are the Pros of Airbyte?

  1. It can handle large amounts of data, allowing organizations to expand without problems.
  2. Users can create their connectors to connect to any data source or destination they require.
  3. Even non-technical individuals may use it easily, thanks to its user-friendly interface and clear instructions.

If you are looking for a highly customizable, open-source data migration solution that supports a wide range of data sources, Airbyte is a fantastic choice. (Also, a cost-effective one!)

8. Informatica Power Center

G2 Rating: 4.4/5 (85 reviews)

 

Informatica PowerCenter rounds out my list of best data migration software.

 

It is well known for its robust performance and high-security standards, built for businesses that deal with complex data environments and require detailed data management. 

  

With its enterprise-grade features, Informatica PowerCenter secures the #8 position on my list.

 

However, the pricing is not available on the company’s website, so it is recommended to contact the team directly.

What are the Key Features of Informatica Power Center?

  1. AI-Powered Automation: The CLAIRE AI engine automates and optimizes data management tasks.
  2. Multi-Cloud, Hybrid Support: Flexible deployment across on-premises, cloud, and hybrid environments.
  3. Metadata-Driven Intelligence: Uses metadata for insights, automating data discovery and improving lineage tracking.

What are the Pros of  Informatica Power Center?

  1. Adaptable to on-premises and cloud migrations.
  2. Effectively manages the movement of large data.
  3. High standards for data security to safeguard private information.

Users appreciate its reliability, automation capabilities, and ability to handle massive data workloads, making it an excellent choice for large-scale, structured migrations. 

What Should You Hire a Data Migration Consultant? 

A Data Migration Consultant is important in ensuring the successful data transfer between different systems. They help you develop a comprehensive migration strategy that aligns with your business objectives.

This involves:

  • Assessing existing data structure
  • Overseeing the execution of the migration process
  • Coordinating with stakeholders to ensure accuracy.

Additionally, Data Migration Consultants provide insights on customizing migration tools to meet your specific needs.

After completing the data transfer process, they offer ongoing support to ensure the new system works properly. Plus, the role of data in digital transformation is crucial, and a data migration consultant helps you use your data effectively in modern systems!

Master the Art of Data Transfer with Data Migration Services 

Choosing an efficient data migration tool is necessary for successful data transfer, especially considering data’s role in digital transformation.

 

Evaluating your needs before selecting a solution that aligns with your organization’s requirements is necessary. 

If you are having trouble choosing the right tool, we highly recommend consulting with a Data Migration Consultant to ensure that you’re all set for critical data migration processes.

 

A Data Migration Consultant’s expertise will guide you in transferring complex data easily.

In fact, if you’re looking for an experienced data migration consultant, we recommend working with an expert from Augmented…

 

Whether you want to migrate your data to a cloud-based server or pivot to a CMS-backed data ecosystem, our data migration consultant will help you figure out the best way to update your legacy systems while safeguarding your data!

So, if you feel you could benefit from the insights of a data migration expert, connect with us for a commitment-free consultation, and we’ll help you devise an end-to-end data migration strategy for your enterprise…

Happy migrating!

8 Best Data Migration Tools 2025: Frequently Asked Questions

1. Are there free data migration tools available?

Yes. There are several free data migration tools available out there. Open-source options like Talend Open Studio and Apache NiFi lets you move data without spending a dime. While they might require some technical expertise, they’re great choices if you’re looking for a cost-effective solution.

2. What is the usual cost associated with data migration services?

The cost of data migration services varies and depends on different factors. It depends on how much data you’re moving, how complex the process is, and what tools or experts you need. Small migrations might be affordable, but large, more complex ones can be expensive. It’s always a good idea to get a quote and plan ahead. 

3. Can I perform data migration without a consultant?

Yes, you can perform data migration without a consultant, but it’s not always the best idea. While small migrations might be manageable, bigger projects with large amounts of data might be a little tricky. A data migration consultant helps prevent data loss, minimizes downtime, and ensures everything runs smoothly. So, if your data is critical, we recommend hiring an expert. 

4. How much time does Data Migration take?

It depends! A simple migration might take just a few hours, while large-scale data migration projects can stretch over days or even weeks. Factors such as data size, system compatibility, and testing time all play a role. The key to a successful migration is good strategic planning, as rushing it can lead to mistakes. 

5. What are the biggest challenges in data migration?

 

Data migration isn’t always smooth sailing. Some of the biggest challenges include data loss, downtime, compatibility issues and security risks. The best way to avoid these problems is to back up your data, test everything beforehand, and use reliable tools. A little preparation goes a long way.

Categories
Accounting Services Blog

Benefits of Outsourced Accounting for Business Owners

There was a time when I used to spend hours trying to balance my finances. Stayed up late and buried in spreadsheets, hoping I wouldn’t miss anything important.

Honestly, it felt like climbing countless mountains. All these tasks pulled me away from what I loved: growing my business.

I know you feel the same I once felt right? That’s when Outsourced accounting came to the rescue. It helped me earn more hours in the day, eased my workload and improved my finances.

How? 

Hang in there, get to the end of this blog and see how accounting outsourcing services are a game-changer for your business. 

What is Outsourced Accounting? 

Outsourced Accounting is when you partner with a team of accountants, experts or business accounting service professionals who take care of your accounting tasks.

 

Instead of handling all your accounting and bookkeeping yourself or hiring an in-house accountant, these professionals handle your accounts remotely.

These experts handle things like:

 

  • Bookkeeping 
  • Tax filing 
  • Payroll management 
  • Account management
  • Financial report preparations
  • Ensure tax compliance 
  • Financial planning ( and more)

What more? As a business owner, you cannot do everything on your own. To run your company effectively, you require someone to handle complicated tasks like accounting. 

Of course, the role of technology in accounting has greatly changed how accounting is done, from manual paper-based to automation and AI. Nonetheless, achieving the right balance between human skills and technology is also a challenge. 

The valuable insights and accounting benefits these professionals provide can help you guide your business decisions. (It did for me.)  Apart from offering many benefits (keep reading for the benefits of outsourced accounting services), the accountants do what they do best so that you can focus on what you do best.

 

Are you ready to hand over your accounting to the experts? Okay, I will list the benefits first. 

Top 9 Benefits of Outsourced Accounting 

500 hours of paperwork saved. 

Flawless, neat and tidy accounts. 

Perfectly managed transactions. 

This is the kind of impact outsourced bookkeeping and accounting can have on your business. 

No matter the size of your industry, many benefits (while some benefits may vary) of outsourced bookkeeping and accounting apply universally to every business. 

Let’s look at 9 bookkeeping benefits that are not just perks but benefits that will propel your business forward. 

Benefit 1: Cost Savings 

Outsource your accounting if you want to save money in the long run. In the start, it may sound counterintuitive. How can hiring an external service save you money?

 

But one of the main bookkeeping benefits precisely is cost savings. How does it work?

  • Reduce overhead costs
  • Savings on salary and other benefits for full-time employees
  • Savings on office space, like desks and computers
  • Reduced software and technological expenses, like software and advanced tools.

The costs of hiring an in-house accountant can add up like a weed and strain your budget with necessities like salary and office space. However, with outsourcing, you can scale the services up and down based on your needs. So, you only pay for the services you need.

Benefit 2: Expert Support 

Recruitment, training and retention. Keeping up with the latest industry rules and best accounting practices. 

That’s a lot, isn’t it? It is difficult to manage all this while running a business. Outsourced bookkeeping professionals specialize in this and take care of it all:

  • Financial management 
  • Tax planning and preparation
  • Handling risk management 
  • Regulatory compliance 
  • Cash flow management ( and more) 

Outsourcing firms have staff who offer unparalleled expertise and help you make skilled decisions based on the latest regulations and best practices. 

Benefits 3: Accuracy and Compliance 

Accounting errors can be more than just a headache. They can spiral into losses and legal penalties.

 

I have seen how these mistakes quickly turn into big fines when there is a lack of in-house expertise or teams are stretched thin. 

Here’s how professional outsourcing firms make sense:

  • Follow a robust accounting system for guaranteed accuracy and minimized errors.
  • Use automated systems for accurate and error-free reporting.
  • They are compliance experts.
  • Guides you with tax codes, legal requirements and obligations.

They won’t let you face severe consequences of inaccurate finances or pay penalties for late or wrong fillings.

Benefit 4: Time-Saving

You are constantly putting out fires. Dealing with unhappy customers, handling employees or other urgent matters.

Then comes the end of the financial year. A stressful time when you want to handle the year-round business fire but also close annual accounts, collect records and documents and put everything in place.

Audits. Taxation. Anxiety. Panic. Your employees might feel overburdened, but accounting professionals are used to these situations. They handle it like a pro.

Without stretching your resources too thin and freeing your time to focus on other things, let professionals handle these tasks. It’s worth considering. 

Benefit 5: Scalability and Flexibility

Your business is bound to change. Your accounting needs are bound to change. Mine did. 

Managing an in-house team is not one of the most practical solutions when you are going through periods of growth, seasonal fluctuations or busy periods during expansions. It’s stressful and not really cost-efficient.

Your employees may feel overwhelmed and overburdened with all the changes. On top of that, you are spending more than you can with the changes.

 

What are the outsourced bookkeeping benefits? They will increase or decrease the level of accounting support you need. They are flexible and scalable. 

Say, during an expansion or tax season, ask them for more support. Conversely, when things are slow, ask them to reduce the level of support. 

Indeed, a very smart way to keep your business running smoothly, no matter the stage you are in your business. 

Benefit 6: Advanced Tech and Tools 

Who doesn’t want to stay competitive in the current market? Staying on the front foot, however, comes with a price to pay.

You have to keep up with the latest technology and tools which becomes difficult for SMEs because investing in high-end software adds up to become a major expense.

That’s one of the major bookkeeping benefits when it comes to outsourcing. They already have access to advanced tools. They use cloud-based systems, real-time financial dashboards and other cutting-edge platforms to keep your finances secure and up-to-date.

Without paying the hefty price, you gain access to these tools while keeping ahead of the competition.

Benefit 7: Better Cash Flow Management

I agree. Poorly managed cash flow causes serious financial problems and puts your business at risk.

How do outsourced bookkeeping accountants help? They provide you with timely reports that are easy to understand.

 

Based on these reports, you can make timely smarter decisions. Where to invest, what to prioritize and when to take on new projects or opportunities.

 

Bookkeeping gives you the confidence to run your business while ensuring that your finances and cash flow are nicely managed. 

Benefit 8: Work on Your Business 

I know from experience that while accounting is necessary, it’s not the only factor that drives your business forward. You also need to focus on delivering the best product or services, providing exceptional customer experience and pushing through the competition.

Therefore, one of the biggest benefits is that you get to focus on the bigger picture. You get to focus on the strategic side of things rather than being stuck only in the details. 

Benefit 9: Better Decision Making

Risks like fraud, mismanagement, and non-compliance can easily set you off track. That’s another major bookkeeping benefit. You don’t have to worry about these challenges.

Benefits of business accounting services also include accurate financial data, tailored insights, better budgeting and performance analysis. The result? You get to make better-informed decisions.

Moreover, these experts also act as strategic partners. They offer advice on cost reduction, financial planning, revenue optimization and more to keep your business running.

What more? If you are looking to expand internationally, outsourced firms are equipped with global expertise. They make the process of cross-border transactions and local requirements easy.

The next question that might come in your head. Who to hire? Is it okay to hire any outsourcing company? Well, no. I have some wisdom for you. Keep reading. 

What Should You Look for When Outsourcing Business Accounting Services? 

There are plenty of benefits of outsourced accounting, but outsourcing companies can cost you a dime. What’s worth considering is you should not get stuck with the wrong one.

 

Consider the following factors when choosing an outsourcing company or consulting firm.

  • Security 

Minor violations can lead to disasters. Do not select a firm that can get into activities that can bring your company down. Check the security features they offer, get it in writing and understand the measures that they offer when it comes to confidentiality. 

  • Cost 

Every firm has and offers a unique pricing plan. Understand their pricing and how much they would pay to the accountant. Are there any hidden costs? Are they transparent with the pricing?

Finally, choose a provider who offers value for the money and is just economical because quality also matters.

  • Expertise and Knowledge

The provider you choose should have the expertise and knowledge, especially for your industry. Ask about their knowledge and industrial experience.

Is the accountant experience enough to handle your growing business? Can they scale as your operations scale and manage the extra work?

  • Customer Reviews and Ratings 

Check for reviews and ratings from current and previous customers. Do you have someone who can give you reviews about the provider? Reputation matters, so consider the number of years they have been providing the services. 

  • End-to-End Accounting Services

Is it payroll management? Is it taxing? Is it accounts payable and receivable? What kind of accounting service are you looking for? Can they provide the service you are looking for? 

Discuss your needs with your current accountant or manager if you have one. Plan and select an outsourcing company that meets your needs.

In the end, you know your company and your finances better. Just make sure that they get back what you expect and need for your business to grow. 

Let Augmented Systems Be Your Growth Partner

Let me be very clear. You really don’t need a whole village to run or manage your accounts. 

You just need someone who can give you quality work in a secure and efficient manner. Augmented Systems has certified accountants with years of experience, proven track record and costs that justify your requirements.

FAQs:

1. Why do companies outsource finance?

Outsourcing your finance and accounting functions can provide numerous benefits, including cost savings, scalability, improved efficiency, and a reduced risk of fraud. 

 

By utilizing the expertise and tools of third-party service providers, your company can achieve a strategic advantage in a competitive market.

 

2. Why is outsourcing necessary?

Outsourcing can help you avoid the one-time costs of hiring and training full-time employees, such as salaries, benefits, and office space. 

 

Outsourcing also allows you to avoid the capital costs of purchasing and maintaining equipment and software needed for specific functions.

 

3. What is the basic concept of outsourcing?

Outsourcing is a business practice where a company hires a third party to perform tasks, manage operations, or provide services.

 

4. What is a risk framework?

The Risk Management Framework is a template and guideline companies use to identify, eliminate and minimize risks. 

It was originally developed by the National Institute of Standards and Technology to help protect the United States government’s information systems.

Categories
Blog Data Migration

What Are the Different Types of Data Migration?

You have your data and know that it needs to be moved. But how? Should you lift and shift, relocate, or copy and paste? 

Torn between the different types of data migration?

With data loss, downtime, unexpected system failure and much more at stake, we know that it’s a tough spot to be in.

The good part? You are in the right place as we break down different data migration types in this blog to help you figure out the best way to migrate your data.

Let’s get going and get you the answer you have been looking for. 

Top 7 Data Migration Types

Data migration isn’t just about moving your data from point A to B. It’s a tricky, complicated process and far more difficult than it appears. Over 80% of the data migration process fails or exceeds its budget. Why such a high failure rate?

 

The truth is that the data migration process is not just a matter of simple copy-and-paste. It requires meticulous data migration planning, strategy and flawless execution.

Each migration is unique, and one wrong decision can lead to complications and unexpected costs. To help you avoid these pitfalls, we have a list of 7 key data migration types, giving you the insights you need to choose the right approach. 

1. Storage Migration

Storage migration is the process of moving data from one storage to another storage location. This data migration process is often done to upgrade old, outdated or legacy hardware to a more modern and efficient system.

It incorporates data protection measures, such as data validation, cloning and eliminating irrelevant or old data.

You can use storage migration to move your data from an on-premise location to a cloud-based platform for faster, higher-capacity storage solutions.

Use Case:

  • Migrating data to cloud storage platforms like Amazon S3 or Microsoft Azure
  • To consolidate multiple storage systems into a centralized solution. 
  • The transition from traditional hard drives to SSDs.

Key Benefits:

  • Improved performance – Enhances the data storage speed
  • Data Integrity – Accuracy and quality data migration
  • Reduced Downtime – Streamlined migration time and minimized downtime
  • Cost Efficiency – No additional license or software required

Key Considerations: 

  • Downtime: Create a data migration strategy to minimize downtime. 
  • Scalability: Choose storage systems that can grow as your business grows.
  • Data Integrity: Data accuracy, consistency and integrity are crucial. 
  • Compatibility: The new storage systems should integrate with your existing system. 

Data Migration Steps: 

  • Data Validation 
  • Data Cloning 
  • Data Cleaning 
  • Redundancy

The storage data migration starts by validating your data for accuracy, quality and consistency between the source and target systems. Next, it creates a clone or replica of the data to prevent risks during transfer.

Outdated or redundant data is then cleaned, and backup copies are finally created to safeguard against potential failure or data loss. 

2. Database Migration

Database migration means transferring data between two distinct database systems. It is done for database systems that frequently need changes to the data language or protocols during the initial data migration.

The change is also visible in the application layer. Database migration modifies or adjusts the data without changing the structure.

Before starting your database migration, incorporate the following steps into your data migration planning.

  • Test the size of the database.
  • Evaluate the apps using the database. 
  • Ensure the confidentiality of your data.
  • Check your data migration strategy for accuracy and compatibility.

Use Case:

  • Migrating from older outdated versions like SQL Server 2008 to newer versions. 
  • Migration of on-premise database to cloud solutions like Amazon RDS or Google Cloud SQL
  • Transitioning from a relational database (like MySQL) to a NoSQL solution.

Key Benefits:

  • Better Performance – Faster queries, optimized indexing and better resource management.
  • Scalibitly – Can handle larger datasets and scale with your business.
  • Improved Security – Better compliance with security standards and data protection rules.
  • Cost Efficient – Reduces maintenance costs and infrastructure overhead. 

Key Considerations:

  • Data Integrity: Validation of your data for accuracy and integrity
  • Downtime: Data migration planning should have minimal disruption
  • Performance Tuning: Optimization of indexes, queries and schema design
  • Compatibility: The new database system must support your existing applications and workflows

Database Migration Steps:

  • Data Assessment 
  • Schema Conversion
  • Data Migration
  • Validation 
  • Performance Testing

A database migration requires serious planning, testing and a proper data migration strategy. The process includes tasks such as analyzing the source database, adjusting the data schema to fit the destination source, maintaining data security and more. 

3. Cloud Migration

Cloud migration refers to moving your data from an on-premise location to a cloud-based storage platform. It also includes migrating your data, applications or services from one cloud location to another.

Use Case:

  • Moving from on-premise systems to the cloud, such as AWS and Google Cloud Platform.
  • Transforming across multi-cloud platforms or environments to avoid vendor lock-in.
  • Migrating scattered datasets to a consolidated and unified cloud platform. 
  • To scale and support global operations. 

Key Benefits:

  • Scalability: Supports growing business needs
  • Cost Efficiency: Cuts operational and maintenance costs. 
  • Enhanced Data Protection: Cloud firewall and security protocols 
  • Remote Accessibility: You can access data from anywhere
  • Performance Optimization: Faster processing and greater flexibility.

Key Considerations:

  • Data Security: Ensure encryption and security protocols to mitigate risks and vulnerabilities. 
  • Compliance: Consider industry-specific security and regulations, such as GDPR or HIPAA.
  • Cost Optimization: To prevent overspending, monitor the cloud resource usage. 
  • Expertise: Hire cloud specialists or train your employees for expertise.
  • Compatibility: Ensure that the legacy system is compatible with the new cloud system. 

Cloud Migration Steps:

  • Assessment 
  • Planning 
  • Data Migration 
  • Testing and Validation 
  • Optimization 

Although cloud migration offers numerous advantages, large migration can take weeks or even months to complete, depending on your system’s complexity and data volume.

Cloud data migration services are becoming increasingly popular due to better storage options, cost savings and flexibility. It is predicted that the global cloud data migration services market will grow from $12.54 billion in 2024 to $69.73 billion by 2032

4. Application Migration

Application migration takes place when you move application software from one computing environment to another. This migration process often involves data transfers between on-premise servers, cloud platforms or different vendors.

This data migration also requires you to transfer not just data but also configurations, dependencies, and interfaces.

Use Case:

  • Moving legacy applications to cloud-based platforms, like AWS, Azure and Google Cloud. 
  • Shifting applications between different cloud providers. 
  • Upgrading from outdated application platforms to modern alternatives. 
  • Switching from one software vendor to another.

Key Benefits:

  • Better Performance: Faster processing, optimized workflows and better performance.
  • Cost Savings: Reduced maintenance and infrastructure costs.
  • Improved Flexibility: You can scale and upgrade your applications for your evolving business needs.
  • Modernization: Improved compatibility with modern technologies and cloud ecosystems.

Key Considerations: 

  • Data Integrity: Use Application Programming Interfaces and vendor tools to ensure data integrity.
  • Dependencies: Identify and manage dependencies on databases, APIs or other applications to avoid disruptions. 
  • Data Compatibility: Data formats and models in the new and old systems should be compatible with each other. 
  • User Experience: Provide training to end-users for better adaptability with the new interface. 

Application Migration Steps:

  • Assessment 
  • Data Mapping
  • API Integration 
  • Testing 
  • Optimization

If you want to modernize your IT infrastructure, enhance your operational performance and reduce costs, application migration is a great option for your migration needs.

5. Business Process Migration

Business process migration takes place when you want to transfer your business data, applications, workflows and operations. It is usually done during mergers and acquisitions or organizational restructuring to reduce costs and improve business efficiency.

Use Case:

  • Integrating workflows, systems and processes post a merger or an acquisition.
  • Moving to modern ERP platforms like SAP or Oracle. 
  • To streamline workflows, eliminate inefficiencies and align processes. 
  • To maintain consistency across processes.

Key Benefits:

  • Enhanced Efficiency: Updated systems reduce redundancies and improve the workflow. 
  • Cost Optimization: Significant cost savings due to consolidated processes.
  • Scalability: Allows you to scale your operations to meet your growing demands. 
  • Standardization: Unified processes across departments, branches and newly merged entities.
  • Competitive Edge: Aligned processes with the latest technologies enhance your agility and market readiness.

Key Considerations:

  • Process Alignment: The migration of processes should align with your business goals and strategies. 
  • Change Management: Clearly communicate and train your employees to onboard the new system.
  • System Integration: To avoid disruptions, seamlessly integrate disparate systems.
  • Testing and Validation: Verify and test all processes, applications and data for the new environment. 
  • Minimal Disruptions: To avoid interruptions to your day-to-day operations, plan the timeliness of your data migration. 

Business Process Migration Steps:

  • Assessment 
  • Planning
  • Integration
  • Testing 
  • Training

During business process migration, one of the key data migration considerations is to focus on process alignment, integrations and change management. Focusing on these factors, you can enhance your workflows and be ready for the competitive market. 

6. Big Data Migration

Big data migration refers to moving structured, semi-structured or unstructured data from one environment to another. You can move your data between on-premise, legacy, cloud and hybrid platforms.

Use Case:

  • Migrating big data to cloud-based platforms.
  • Moving from traditional databases to advanced tools, like Spark or Snowflake.
  • Combining data from multiple sources or silos into a centralized data lake. 
  • Migrating big data for real-time data processing and analytics.

Key Benefits:

  • Reduced Expenses: Reduced labor, hardware and maintenance costs. 
  • Business Agility: Keeps your business moving without being locked up on a particular application or platform. 
  • Centralized storage: Breaks data silos to bring your business into one single spot. 

Key Considerations:

  • Data Security: Opt for the right security measures to protect your data while migrating. 
  • Technical Skills: Hire a technical expert or data migration consultant with intense knowledge of data migration tools and practices. 
  • Downtime Management: Plan your migration with minimal disruption to your business. 
  • Expenses: Integrating each application to move your data traffic is expensive and time-consuming.

Big Data Migration Process Steps:

  • Planning
  • Preparation
  • Design
  • Execution
  • Training

The best data migration practices will help you unlock your data’s true potential and make it work well. Proper planning allows you to transition to an efficient, scalable and modern platform using big data migration. 

7. Data Center Migration

Data center migration occurs when IT assets, applications, workloads and datasets are transferred from one data center to another. It can also involve moving between physical locations, modernizing infrastructure and moving to cloud-based data centers.

Use Case:

  • Transferring your IT infrastructure to a new data center or computing environment.
  •  Shifting operations or entire data centers to cloud-based data centers.
  • A company merger or an organizational expansion.
  • Migrating for disaster recovery by data backup. 
  • To modernize the existing infrastructure for regulatory requirements.

Key Benefits:

  • Minimal Downtime: Established processes and tools, scheduling and execution for minimzed downtime. 
  • Reduced Costs: Less operational and maintenance costs. 
  • Security and Compliance: Safeguards data and ensures regulatory compliance. 
  • Scalability: Scalable solutions to accommodate your growing business. 
  • Energy Efficiency: Consumes less energy and reduces environmental impact.

Key Considerations:

  • Downtime Management: Thoroughly plan the migration to reduce downtime. 
  • Asset Mapping: Check all kinds of discrepancies, including hardware and software issues. 
  • Data Security: Protect your data with robust encryption and security protocols. 
  • Capacity Planning: Ensure that the new data center has enough capacity for current and future workloads. 
  • Testing: Check for performance, application functionality and reliability post-migration. 

Data Center Migration Steps: 

  • Assessment and Analysis
  • Designing the Destination Environment 
  • Data Migration 
  • Testing and Validation 
  • Monitoring and Support

A well-planned data center migration is a reliable migration strategy that helps improve operational performance and efficiency. It can also reduce costs, modernize IT infrastructure, and improve operations.

Conclusion

No matter the type of data migration you choose, understanding the concept, choosing the right approach and selecting the right tools is the key to a successful migration.

Instead of rushing into the migration, it is always good to plan, think proactively and consider the possible risks.

Finally, finding the appropriate strategy is up to you and your business goals and needs. Are you planning to upgrade? Contact our team of data migration specialists at Augmented Systems today.

FAQs: 

 

1. What are the three stages of data migration?

The three basic stages of data migration include: 

 

  • Data Extraction 
  • Data Transformation
  • Data Loading

2. What are the main phases of data migration?

The main phases of data migration include: 

 

  • Preparing for the migration
  • Planning for the migration
  • Migration 
  • Operation and Optimization

3. What is migration in SQL?

SQL data migration is defined as moving data from one SQL server database to another. The data migration process looks easy at first, but it involves a lot of complexity, especially when migrating a large volume of data. 

 

4. What is the risk of data migration?

Data migration is a complex process that helps you transfer your data from your legacy system to a new system. It comes with risks, such as:

 

  • Data loss
  • Downtime
  • Data incompatibility 
  • Manual interfaces and more.

5. What happens after data migration?

After the data migration process is complete, you eventually abandon your old, legacy system or database.