Presenting data in Excel vs. preparing it for Power BI: key differences

Although Excel and Power BI are complementary tools within the data analysis ecosystem, the way data is structured and presented changes significantly depending on the goal. Excel is designed for direct work and visualization, while Power BI requires a more model-driven and scalable analytical approach.

Excel: direct and flexible presentation

In Excel, data is typically presented with a visual and immediate approach:

• Use of merged cells, colors, and formatting for emphasis.

• Tables that mix values, headers, and totals in the same sheet.

• Reports built manually with visible formulas and limited reusability.

• Structures optimized for human reading, not automated analysis.

  
  

Power BI: clean, consistent, relational data

Power BI doesn’t “read” aesthetics; it needs structure:

• Tables in a “database-like” format: one row = one record, one column = one attribute.

• No merged cells, manual totals, or formatting tricks.

• Data separated into logical tables (facts, dimensions) to build a relational model.

• Uniform headers, defined data types, and no improvised calculations.

• A design oriented toward automation and refreshability.

  
  

The key: Excel presents, Power BI models

In Excel, you can mix presentation and data in the same sheet. In Power BI, the presentation (visuals) is separated from the data model, which requires tables to be clean, coherent, and analytically structured.

Conclusion

Moving from Excel to Power BI is not just switching tools—it’s shifting mindset. Excel allows manual report building; Power BI demands thinking in terms of data quality, modeling, relationships, and automation.