Excel
Lab 2.3: Excel
Section titled “Lab 2.3: Excel”Generate narrative insights from spreadsheet data
Start the Lab
Section titled “Start the Lab” Process Excel spreadsheets
/CC.m2.lb3 What You’ll Learn
Section titled “What You’ll Learn”- Describe the difference between data, information, and insight, explaining how context transforms raw numbers into actionable business understanding
- Apply the xlsx skill with appropriate business context to generate narrative summaries that answer specific questions rather than producing generic analysis
- Analyse AI-generated insights critically, verifying key numerical claims against source data and identifying where caveats or limitations should be noted
Key Concepts
Section titled “Key Concepts”| Concept | Description |
|---|---|
| Data vs. Information vs. Insight | Data is raw numbers; information is organised, contextualised data; insight is actionable understanding that supports decisions. |
| Business Context | Providing specific business questions and context transforms generic data descriptions into meaningful, actionable analysis. |
| Trust but Verify | AI-generated insights require critical evaluation; always spot-check important numbers against the source spreadsheet. |
| Data Quality Notes | Documenting normalisations, assumptions, and inconsistencies makes analysis honest and more useful for readers. |
| Weighted Pipeline Value | Pipeline value adjusted by win probability, giving a more realistic forecast than raw totals. |
What You’ll Create
Section titled “What You’ll Create”pipeline-insights.md- Narrative insights document
Eureka Moment
Section titled “Eureka Moment”“I asked it a specific question and got an answer I could actually use in a meeting - not just a list of numbers!”
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