Excel vs Power BI Comparison: Which Tool for Your Data?

Introduction

In a world increasingly oriented towards data analysis , having powerful tools to collect, process and visualize information has become crucial. For decades, Excel has established itself as one of the most emblematic software for manipulating tables and performing calculations. For its part, Power BI , more recent, presents itself as a Business Intelligence (BI) tool capable of manipulating large volumes of data and offering dashboards with interactive visualizations.

Despite their common affiliation (both developed by Microsoft), these two tools do not always address the same needs or the same audiences. In this article, we will explore the specificities of each tool, highlight their strengths and limitations, then identify avenues to help you make an informed choice, or even consider a complementary use of Excel and Power BI depending on the nature of your projects.

Comparison of the two tools

When it comes to choosing between Excel and Power BI, it’s helpful to compare their key features, benefits, and limitations. The table below provides a summary overview of the major differences. We’ll then break these points down to better understand in which situations each of these tools is most suitable.

Data analysis and manipulation

• Excel : Remains a go-to tool for small-scale calculations, formulas, and data analysis. Users can apply complex formulas and create pivot tables, but Excel quickly shows its limitations when it comes to processing millions of rows or managing large databases.
• Power BI : Designed to handle large data sets, it integrates Power Query (for data preparation and transformation) and DAX (for advanced calculations). This structure makes it easy to assemble and consolidate information from various sources (SQL, API, flat files, etc.).

Visualizations and Dashboards

• Excel : Offers basic charts (histograms, lines, pie charts, etc.) and limited interactivity. Users who want more advanced features must use VBA macros or add-ins. To learn how to create one, see the guide to creating an Excel dashboard .

• Power BI : Shines with its rich interactive visuals and the ability to create dynamic dashboards. Users can drill down to dig into data, while maintaining an overview with intuitive filters and segments. To learn how to create, check out the guide to creating a Power BI dashboard .

Real-time analysis and automation

• Excel : Spreadsheets present static data. Refreshing a table usually requires reloading the file or using external connections (OLE DB, queries, etc.). Automating reports often requires macros or third-party tools.
• Power BI : Has a scheduled refresh solution and can manage real-time monitoring via Power BI Service. Coupled with Power Automate (Microsoft tool included in Power Platform ), it allows you to trigger workflows and automated alerts, making KPI monitoring more proactive.

Collaboration and sharing

• Excel : Historically, workbook sharing was done via email or OneDrive, with a risk of version conflicts. Real-time co-editing exists, but remains less fluid than a 100% cloud tool.
• Power BI : Fully designed for online collaboration. Reports and dashboards are accessible via Power BI Service, with workspaces dedicated to co-construction. Users can comment, ask questions and receive updates in real time.

Cost and licenses

• Excel : Often included in the Microsoft Office suite, either through a one-time purchase or a Microsoft 365 subscription. It is a tool that is already present in most companies, which reduces the additional implementation cost.
• Power BI : The basic version (Power BI Desktop) is free, but access to advanced sharing or collaboration features (Power BI Pro, Premium) requires a monthly or annual subscription. Costs can therefore climb depending on the size of the company and the number of users.

Learning curve and integration

• Excel : Widely used for decades, it is familiar to most professionals. The basic features are intuitive, but going further (macros, VBA) takes time and practice.
• Power BI : Requires understanding of business intelligence logic (modeling, DAX, table relationships, etc.). This learning curve is steeper, but once mastered, the tool allows you to create interactive and large-scale reports. In addition, it integrates perfectly with the Microsoft ecosystem (Azure, Dynamics, etc.), which can offer a strategic advantage for companies already engaged in these technologies.

Examples of Excel and Power BI dashboards

Project management

In a project management environment, it is essential to track indicators such as progress, costs and resource allocation in order to anticipate risks and delays. An effective dashboard gives a global vision of the project and allows for better decision-making.

Excel is best suited for data stored in a single file. Pivot tables and filter slicers make it easy to analyze tasks and expenses, and creating simple charts helps visualize how your schedule is progressing. However, it is limited if the project involves frequent updating of information or if multiple people are working on the same document at the same time. See this example of an Excel Project Management tool.

Power BI , more complex to learn, allows you to connect multiple data sources via Power Query and manage large volumes of information in real time. Advanced filters and interactive visualizations offer a more dynamic dashboard, while online collaboration ensures continuous monitoring of the project for all stakeholders. See this example of a Power Bi Project Management tool .

AMDEC Risk Analysis (FMEA)

AMDEC , or FMEA, aims to identify and prioritize potential failures within a process or product in order to implement corrective actions. A clear dashboard makes it possible to quickly target the most critical risks and monitor the progress of their treatment.

By centralizing data in a single workbook, Excel makes it easy to calculate criticality indices (severity, frequency, detectability) and create modern dashboards using pivot charts, which filter different failure modes. The use of segments facilitates filtration by period, but the tool shows its limits if you want to automate data collection or consolidate multiple sources dynamically.

Power BI offers greater flexibility to connect different databases and automatically combine information related to failure modes, corrective actions or feedback. In our case, using the Excel file previously used as a data source, the Power Query interface allows you to transform and clean the data upstream, while advanced filters and interactive visuals ensure in-depth analysis, especially when it comes to spotting trends or comparing the evolution of criticality over time.

Example used in this video:

Excel - AMDEC Excel Process - IPR Monitoring Dashboard

Power bi - Power BI template - Risk analysis (Amdec)

OEE monitoring

OEE (Overall Equipment Effectiveness) is a key industrial performance indicator that measures the availability, performance and quality of a production line. A dedicated dashboard helps to quickly identify bottlenecks and improve overall efficiency.

When production data is centralized in a single file, Excel can calculate OEE using formulas and create graphs to visualize changes in availability or scrap rates. Pivot tables can refine analyses using dynamic dashboards, but updating remains manual and can quickly become time-consuming if you work on many sites or machines.

With Power BI , it is possible to directly link data from an MES system or other production databases, without going through manual consolidation. The advanced organization of Power Query makes it easy to manage large volumes and create complex filters, while interactive visuals provide a real-time view of OEE. Online collaboration reinforces the proactive aspect, because maintenance and production teams can be alerted and react immediately in the event of a significant deviation.

Example used in this video:

Excel - Power Bi Project Management Template to download

Power Bi - Power BI Template - TRS (Overall Earnings Ratio) Tracking

Choosing the right tool for your needs

Criterion 1: Data volume

• Small or medium quantity: Excel is still sufficient.

• Large bases: Power BI is more suitable.

Criterion 2: Need for collaboration

• Limited collaboration, manual versioning: Excel can be suitable.

• Real-time teamwork, shared dashboards: Power BI is more powerful.

Criterion 3: Budget and licenses

• Excel is usually included in the Office suite, often already paid for by the company.

• Power BI requires a subscription (Pro or Premium) for some advanced features.

Criterion 4: Skills and learning

 

• Team accustomed to Excel: Low learning curve.
• Ambitious BI project: Power BI training recommended.

Summary Advantages and Disadvantages

Tool	Benefits	Disadvantages
Excel	- Easy to handle - Very widespread in business - Versatile and flexible	- Limited in the face of large volumes of data - Sometimes complex collaboration - Risk of human errors
Power BI	- Interactive dashboards - Manages large databases - Advanced collaboration	- Steeper learning curve - Cost (Pro/Premium licenses) - Need for a suitable environment

Conclusion

Excel and Power BI are two complementary tools. Excel is ideal for quick analyses, daily reports or small volumes of data. Power BI, on the other hand, stands out for larger-scale business intelligence, real-time collaboration and advanced visualizations.

Recommendation : Assess your needs in terms of data volume, collaboration, budget and skills to choose the most suitable tool, or consider a combined use of both solutions when this makes sense.