Excel vs. Google Sheets vs. Power BI: Key Differences, uses 📚

  Comparison of Excel, Google Sheets, and Power BI in tabular format, highlighting their key features, uses, and differences:

Excel vs. Google Sheets vs. Power BI: Key Differences

Feature	Microsoft Excel	Google Sheets	Power BI
Primary Use	Spreadsheet calculations, data organization	Cloud-based collaboration, lightweight analytics	Business intelligence, interactive dashboards
Deployment	Desktop/Online (Office 365)	Cloud-only	Desktop (Power BI Desktop) + Cloud (Power BI Service)
Collaboration	Limited real-time co-editing (via Excel Online)	Real-time collaboration with comments & history	Limited (requires Power BI Service for sharing)
Data Capacity	~1M rows (varies by version)	~10M cells (slows with large data)	Handles millions of rows (optimized for big data)
Formulas & Functions	Advanced (XLOOKUP, Power Query, VBA)	Similar to Excel but fewer advanced functions	DAX (Data Analysis Expressions), M language
Visualizations	Basic charts & PivotTables	Basic charts & limited PivotTables	Interactive dashboards, custom visuals, AI-driven insights
Automation	Macros (VBA)	Apps Script (JavaScript-based)	Power Query, Power Automate integration
AI Integration	Excel Ideas (basic AI insights)	Explore (simple AI suggestions)	AI visuals, Q&A (natural language queries)
Cost	Paid (one-time or Office 365 subscription)	Free (with Google account)	Free (Power BI Desktop) / Paid (Pro/Premium)
Best For	Financial modeling, complex calculations	Team collaboration, quick edits	Enterprise analytics, real-time reporting

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When to Use Each Tool?

1. Microsoft Excel

• Use Cases:

  • Complex financial models.

  • Data cleaning with Power Query.

  • Advanced statistical analysis.

• Pros:

  • Offline access.

  • Robust formulas (VBA, Power Pivot).

• Cons:

  • Limited real-time collaboration.

2. Google Sheets

• Use Cases:

  • Team-based data entry.

  • Simple dashboards with connected apps (Google Data Studio).

• Pros:

  • Free & accessible anywhere.

  • Version history & easy sharing.

• Cons:

  • Slows with large datasets.

3. Power BI

• Use Cases:

  • Interactive business dashboards.

  • Merging data from multiple sources (SQL, APIs, Excel).

• Pros:

  • Handles big data efficiently.

  • AI-powered analytics.

• Cons:

  • Steeper learning curve.

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Summary Table: Which Tool to Choose?

Need	Excel	Google Sheets	Power BI
Complex calculations	✅ Best	❌ Limited	⚠️ Possible (DAX)
Real-time collaboration	❌	✅ Best	⚠️ (Cloud-only)
Big data analytics	❌	❌	✅ Best
Free to use	❌ (Paid)	✅ Yes	✅ (Desktop)
Automation & AI	⚠️ (VBA)	⚠️ (Apps Script)	✅ Best

Final Tip:

• Use Excel for deep analysis.

• Pick Sheets for teamwork.

• Choose Power BI for scalable BI solutions.