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Power BI VS. Excel - Explained
Updated on 26th May, 23 20 Views

In this blog, we will explore the key differences between Power BI and Excel to help you make an informed decision on which one to choose for your data analysis requirements.

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What is Power BI?

Power BI is a business intelligence and analytics tool that helps to effectively analyze data, create reports, and build dashboards in an easy and accessible way.

Power BI enables businesses to extract insights from their data and helps them make efficient decisions. It connects to a wide variety of data sources and provides data modeling tools to transform and clean the data.

Users can then visualize the data through rich reports that contain charts, maps, key performance indicators, and other visuals. Dashboards in Power BI bring multiple reports and visuals onto a single screen, providing an at-a-glance view of key metrics and information. 

Reports and dashboards in Power BI can be shared with other users in an organization through the Power BI service. This sharing and collaboration enable different teams and departments to have a central place for all of their key analytic content and insights. With Power BI, businesses can democratize data and analytics, empowering more users across the organization.

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What is Excel?

Excel is an electronic spreadsheet application developed by Microsoft. It allows users to organize, format, and calculate data with formulas using a grid of cells in rows and columns. Excel workbooks can contain one or more worksheets, each consisting of up to 1,048,576 rows and 16,384 columns.

Excel provides tools to manipulate data for analysis, reporting, and tracking. It can connect to external data sources and import data to build advanced models and dashboards. 

Formatting options in Excel allow users to customize the look of worksheets through features such as colors, fonts, styles, borders, and headers and footers. Formulas can perform calculations with cell references, functions, operators, and constants.

Common Excel functions include SUM, AVERAGE, COUNT, MAX, MIN, IF, and many others. Excel also features charts and graphs that visualize data in various formats like columns, lines, pies, bars, and more. 

With Excel Macros, users can automate repetitive tasks through the recording and running of VBA (Visual Basic for Applications) code. Overall, Excel allows users to store, organize, manipulate, and present data in a flexible and customizable way.

Key Differences Between Power BI and Excel

Data Visualization

One of the main differences between Power BI and Excel is the approach toward data visualization. Power BI creates dynamic and interactive visualizations, while Excel provides static charts and graphs.

One of the most significant differences between Power BI and Excel is their approach to data visualization. Power BI is designed to create dynamic and interactive visualizations, while Excel is more focused on creating static charts and graphs.

Power BI’s drag-and-drop interface allows users to create interactive visualizations quickly and easily, it also helps to explore data in real-time, filter data points, and drill down into specific data subsets. Power BI is an excellent tool for data exploration and analysis due to its ability to create dynamic visualizations.

Excel’s charts and graphs are more suitable for straightforward data representation and lack the interactive features of Power BI. While Excel does offer some interactive visualization options, such as slicers and timelines, they are not as dynamic as Power BI’s visualizations.

Data Handling

Power BI and Excel are both business intelligence tools, but they excel at slightly different things. Power BI is better suited for analyzing large datasets and gaining enterprise-wide insights, while Excel excels at manipulating and formatting smaller datasets.

Power BI connects directly to data warehouses, databases, and cloud data sources to pull in massive amounts of data. Later, it can transform and shape that data using sophisticated data modeling capabilities. This makes Power BI a powerful tool for gaining high-level insights that span an entire organization.

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Power BI reports and dashboards can then be published and shared company-wide to distribute those insights. By contrast, Excel works best with datasets with thousands to millions of rows. While Excel does allow for the analysis and visualization of data through functions, charts, and pivot tables, it struggles to efficiently handle and calculate extremely large datasets. 

Excel truly shines for ad hoc analysis of medium-sized datasets, formatting and styling spreadsheets, and creating customized reports at a smaller scale. 

Power BI and Excel form a harmonious partnership, each playing a distinct role in the realm of data analysis. Power BI excels in providing robust analytics capabilities for vast data sets at an enterprise level, while Excel thrives in facilitating focused analysis, reporting, and visualization of medium-sized data sets. Together, they offer a comprehensive and complementary toolkit for diverse data needs.


Power BI offers several collaboration features that are not available in Excel. The Cloud-based services of Power BI allow users to share dashboards and reports with other users, enabling collaborative data analysis. 

Power BI also allows users to set up data alerts, which can be triggered when specific data points meet certain criteria. This feature is particularly useful for monitoring business operations in real time.

Excel, on the other hand, is primarily a desktop application, which can limit collaboration between users. While Excel does offer collaboration features, such as co-authoring and sharing via OneDrive, it is not as robust as Power BI’s collaboration features.

Power BI Advantages over Excel

While both Power BI and Excel are powerful tools for data analysis, Power BI has several advantages over Excel. 

  • Real-Time Data Insights – Power BI can connect to live data sources, allowing for up-to-the-minute analytics and dashboards. As new data comes in, Power BI automatically refreshes reports and visualizations so users always have the latest insights. This makes Power BI well-suited for monitoring business performance in real-time.
  • Interactive Visualizations – Power BI’s visualizations are dynamic, interactive, and linked. Users can filter, sort, and navigate between visuals to explore data from different angles. This interactivity helps users gain a deeper understanding of complex data relationships and uncover insights that may not be obvious from static reports.
  • Ability to Handle Large Datasets – Power BI is built to ingest, transform, and analyze massive amounts of data. It can efficiently handle datasets with millions of rows, enabling enterprise-wide analytics.

    This means Power BI can provide a comprehensive view of insights across an entire organization. Excel, on the other hand, struggles with very large datasets and is mainly suited for medium-sized data analysis.

The key advantages, such as real-time data, interactive visualizations, and big data capabilities,  make Power BI a superior tool for gaining true insights into business operations and performance. 

Power BI’s features go beyond traditional reporting to provide a dynamic and comprehensive view of data that helps inform critical business decisions.

Excel Advantages over Power BI

Excel Advantages over Power BI

Excel offers more flexibility, customization, familiarity, ease of use, compatibility, and formatting options compared to Power BI. However, Power BI excels at tasks that require real-time insights, interactive visualizations, and the ability to handle massive datasets. Each tool has its advantages for different types of data analysis needs.

Here are some advantages Excel has over Power BI:

  • Flexibility and Customization – Excel allows for a high level of flexibility and customization. Users have full control over formatting, styling, adding graphical elements, and arranging data. Excel spreadsheets can be tailored to specific needs and use cases. Power BI offers less flexibility and some predefined report templates.
  • Familiarity – Excel is a more common and familiar tool for many users. People who already know Excel can transition more easily to working with data in spreadsheets. Power BI has a slightly different environment and set of features that may require more learning.
  • Ease of Use – Excel is generally considered an easier and more intuitive tool to use, especially for simple tasks. The spreadsheet interface is easy to understand. Power BI can be more complex and requires learning new software.
  • Compatibility – Excel has better compatibility with other Office products and file formats. Users can easily share Excel workbooks with others and insert Excel data into Word or PowerPoint. Power BI reports have less compatibility outside of the Power BI ecosystem.
  • Formatting – Excel allows for more precise and robust formatting and styling options. Users have full control over things like cell margins, text wrapping, conditional formatting, and other advanced styles. Power BI’s formatting is limited.
  • Macros and Functions – Excel has a rich library of built-in functions as well as the ability to create macros using VBA. This gives Excel advanced programmability that Power BI lacks.

Power BI or Excel – Which One to Choose?

Both Power BI and Excel have advantages. Power BI offers advanced capabilities for enterprise-wide big data analytics, whereas Excel provides an accessible environment for analyzing smaller, less complex datasets. Consider your individual needs and use each tool to its greatest extent to get the most out of your data.

The right choice between Power BI and Excel comes down to your unique analysis needs and data.

Power BI excels at complex datasets, interactive reports, and collaboration. If your requirements include:

  • Significant data volumes from multiple sources that change frequently
  • The need to identify patterns, trends, and anomalies across large amounts of data
  • Interactive visualizations to explore different angles of your data
  • Sharing insights with others in your organization

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Then Power BI is likely the best option. Its ability to model large complex datasets and create dynamic visualizations will enable more in-depth analysis and actionable insights.

Excel works best for simpler, ad hoc analysis of medium-sized datasets. If you need:

  • Flexibility to format and style data exactly how you want
  • A spreadsheet interface that is intuitive and easy to use
  • Compatibility with other Office tools

Then Excel will be the more straightforward choice. While it lacks some of Power BI’s advanced analysis capabilities, Excel offers a versatile, customizable, and productive environment for medium-sized data tasks.


To summarize, both Power BI and Excel are effective data analysis tools, and the choice between the two depends  on your requirements. 

Power BI excels at huge datasets and real-time data insights, whereas Excel excels at smaller datasets and clear data representation. Understanding the fundamental differences between Power BI and Excel is critical when deciding which tool to utilize for your data analysis needs.

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