Spreadsheets, AI, and When to Use What
Different tools suit different tasks. This chapter helps you choose and combine tools effectively.
The Tool Landscape
Spreadsheets (Excel, Google Sheets)
Best for:
- Smaller datasets (under ~100,000 rows)
- Ad-hoc analysis
- Familiar, accessible
- Calculations with formulas
- Basic charts
- Manual data manipulation
Limitations:
- Performance with large data
- Complex analysis
- Version control
- Collaboration challenges (Excel)
AI Assistants (Claude, ChatGPT, etc.)
Best for:
- Natural language questions
- Explaining concepts
- Suggesting approaches
- Pattern recognition
- Data cleaning suggestions
- Generating code
- Interpreting results
Limitations:
- Context window limits
- Can make mistakes
- Need to verify outputs
- Not connected to live data
Business Intelligence Tools (Tableau, Power BI, Looker)
Best for:
- Dashboards and visualization
- Large datasets
- Shared reporting
- Regular monitoring
- Interactive exploration
Limitations:
- Learning curve
- Cost
- Setup required
- Less flexible for ad-hoc
Programming (Python, R, SQL)
Best for:
- Complex analysis
- Large datasets
- Reproducibility
- Custom modeling
- Automation
Limitations:
- Learning curve
- Setup overhead
- Slower for simple tasks
When to Use What
Quick, One-Time Analysis
Start with: Spreadsheet or AI
Small dataset, simple question, don't need to repeat? Open Excel or paste into AI.
Regular Reporting
Use: Spreadsheet templates or BI tools
Build once, refresh regularly. Templates save time.
Exploring New Questions
Use: AI first, then spreadsheet or code
AI helps you figure out the approach. Then execute with appropriate tool.
Large Dataset
Use: BI tool or programming
Spreadsheets slow down with large data. Use tools designed for scale.
Learning New Techniques
Use: AI for explanation, then practice in tools
AI explains concepts clearly. Then apply in real tools.
Combining Tools Effectively
The AI + Spreadsheet Workflow
- Plan in AI: Ask AI how to approach the analysis
- Prepare in spreadsheet: Clean and structure data
- Analyze with both: Use AI for complex questions, spreadsheet for calculations
- Verify: Check AI outputs against spreadsheet calculations
- Communicate: Use AI to help draft summaries
Using AI with Spreadsheets
Getting help:
- "Write an Excel formula to [calculation]"
- "How do I create a pivot table for [task]"
- "What's wrong with this formula: [formula]"
Analysis:
- Paste data into AI
- Ask questions
- Request calculations
- Get interpretation
Practical Spreadsheet Tips
Essential Functions
SUMIF/SUMIFS: Sum based on criteria COUNTIF/COUNTIFS: Count based on criteria AVERAGEIF: Average based on criteria VLOOKUP/INDEX-MATCH: Look up values IF: Conditional logic TEXT/VALUE: Convert between text and numbers CONCATENATE/&: Combine text
Pivot Tables
The most powerful spreadsheet feature. Learn it well.
Use for:
- Summarizing by categories
- Cross-tabulations
- Quick calculations
- Data exploration
Data Validation
Prevent errors by restricting inputs:
- Drop-down lists
- Number ranges
- Date restrictions
Named Ranges
Name your data ranges. Makes formulas readable.
Workflow Examples
Example 1: Monthly Sales Report
- Export sales data from system (CSV)
- Open in spreadsheet
- Clean: remove duplicates, fix formats
- Create pivot table: sales by product/region
- Add month-over-month comparison
- Create charts
- Use AI to help write summary
- Share report
Example 2: Customer Segmentation
- Export customer data
- Paste sample into AI: "How should I segment these customers?"
- AI suggests RFM approach
- Calculate RFM scores in spreadsheet
- Ask AI: "How do I categorize these scores?"
- Apply categorization in spreadsheet
- Analyze segment differences
- Create recommendations
Example 3: Ad-Hoc Question
- Business question arises
- Identify needed data
- Paste into AI: "What's the relationship between X and Y?"
- AI provides analysis and interpretation
- Verify key numbers in spreadsheet
- Communicate findings
AI Prompt: Tool Selection
Help me choose the right approach for this analysis.
What I need to do: [Analysis task]
Data size: [Approximate rows/complexity]
My tools: [What you have access to]
My skills: [What you're comfortable with]
Timeline: [How quickly needed]
Repeatability: [One-time or ongoing]
Recommend:
1. Best tool/approach for this task
2. Step-by-step workflow
3. What to watch out for
4. Alternatives if primary approach doesn't work
What's Next
Templates for common analyses.
Next chapter: Analysis templates.

