I recently blogged extensively about creating interactive dashboards in Excel, and why you might want to do that. But if you’re seriously thinking about taking the leap from Excel to Power BI, this blog might help. I summarise the 5 main differences between Power BI vs. Excel, then share 7 powerful things Power BI can do that Excel can’t.

“If all you have is a hammer, everything looks like a nail.” – Abraham Maslow

5 Main Differences Between Power BI and Excel

The following summarises the five main differences, highlighting the distinct strengths and purposes of Power BI and Excel. In essence, Power BI is more focused on advanced data visualisation and business intelligence, while Excel remains a versatile tool for general-purpose data analysis and reporting. But they both exist in their own right to serve different audiences and complement each other.

1: Purpose and Focus

Excel: Excel is a general-purpose spreadsheet software primarily used for data entry, calculation, analysis, and reporting. It’s commonly used for tasks like budgeting, accounting, team reports, and creating charts and tables based on small- to medium-sized datasets (i.e. less than 100,000 data records).

Power BI: Power BI is a business analytics tool focused on comprehensive data visualisation, interactive dashboards, and business intelligence (BI). It’s designed for analysing large datasets (millions of records), creating dynamic reports, and gaining insights from data to make data-driven decisions.

2: Data Size and Performance:

Excel: While Excel can handle moderate-sized datasets, performance degrades when dealing with very large datasets or complex calculations. Especially when using typical computers with 4GB – 8GB RAM. Excel is more suited for smaller-scale data analysis tasks; typically for the tens-of-thousands of records or less.

Power BI: Power BI is optimised for handling large volumes of data and performing complex calculations efficiently. It can handle millions of rows of data and is designed to deliver high performance, even with large datasets and complex data models.

3: Data Modelling and Relationships

Excel: Excel offers basic data modelling capabilities, such as creating simple tables, formulas, and pivot tables. However, it lacks robust features for defining relationships between data tables and creating sophisticated data models.

Power BI: Power BI provides advanced data modelling capabilities, allowing users to create relationships between multiple data tables, define calculated columns and measures using DAX (Data Analysis Expressions), and build complex data models for analysis.

4: Visualisation and Interactivity

Excel: Excel offers basic charting and visualisation features, allowing users to create static charts and graphs. You can create better charts with some practice too. While it provides some interactive features, such as pivot tables and slicers, the level of interactivity is limited compared to Power BI.

Power BI: Power BI provides a wide range of interactive and customizable data visualisation options, including various chart types, maps, and custom visuals. Users can create dynamic dashboards and reports with interactive features like drill-down, cross-filtering, and custom tooltips. However, be prepared for a big learning curve on this!

5: Sharing and Collaboration

Excel: Excel files are typically shared as standalone files, such as .xlsx or .csv files. While multiple users can collaborate on an Excel file simultaneously using tools like Excel Online, SharePoint, or the hellhole of Teams, collaboration features are somewhat limited.

Power BI: Power BI offers robust sharing and collaboration features, allowing users to publish their reports and dashboards to the Power BI service. Reports can be shared with colleagues, accessed from anywhere, and viewed on various devices. Power BI also supports collaboration features such as commenting, sharing insights, and data governance. These features are far more expensive for companies though.

7 Things Power BI Can Do Better than Excel

Power BI and Excel are both powerful tools for data analysis, but they have different strengths and are designed for different purposes. In my detailed blog and video series arguing the case for making stunning, dynamic dashboards in Excel, there are some limitations to the ‘Excel way’.

If you do have the time, money, and inclination to plough effort instead into the steeper learning curve of Power BI, there will be greater rewards later. Here are 7 key capabilities of Power BI that Excel doesn’t offer:

  1. Advanced Data Visualisation: Power BI provides more advanced and interactive data visualisation capabilities compared to Excel. It offers a wide range of customizable visualisations and interactive features such as drill-down, cross-filtering, and custom tooltips.
  2. Real-Time Data Analysis: Power BI can connect to live data sources and perform real-time analysis. It allows you to create dashboards and reports that automatically update as new data becomes available, providing insights into current trends and performance.
  3. Data Modelling and Relationships: Power BI has robust data modelling capabilities, allowing users to create relationships between different data tables, define calculated columns and measures using DAX (Data Analysis Expressions), and build complex data models for analysis.
  4. Data Transformation and Cleansing: While Excel offers some data transformation features, Power BI provides more advanced capabilities for data cleansing, shaping, and transforming data from multiple sources using its Power Query Editor. It allows users to perform complex data transformations and apply steps to automate data preparation processes.
  5. Sharing and Collaboration: Power BI offers better sharing and collaboration features compared to Excel. Users can publish their reports and dashboards to the Power BI service, where they can be shared with others, accessed from anywhere, and viewed on various devices. Power BI also supports collaboration features such as commenting, sharing insights, and data governance.
  6. Large-Scale Data Analysis: Power BI is optimised for handling large volumes of data and performing complex calculations efficiently. It can handle data sets that are too large or complex for Excel to process effectively, up to millions of data records, making it suitable for enterprise-level analytics and business intelligence solutions.
  7. Integration with Other Tools: Power BI integrates seamlessly with other Microsoft products and services such as Azure, SQL Server, Dynamics 365, and Office 365, as well as third-party applications and services. This integration allows users to leverage existing data sources and workflows and build end-to-end data solutions.

So in summary, Power BI is designed for organisations and users requiring advanced data analysis, interactive visualisations, and business intelligence capabilities. Excel on the other hand remains a far more familiar and versatile tool for general-purpose data analysis and reporting, which can be made less boring with a little skill enhancement.

But one thing I bet you didn’t know that Excel can do but Power BI can’t: Save masses of time on data entry by importing data from just an image file! I hope you found this blog helpful.

Kind Regards, Adrian

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