2.4 Data to Narrative

Time: ~25 minutes

What You'll Learn

• The structure of a good data narrative (and why bullet points aren't enough)
• How to have AI draft a summary tailored to your specific audience
• Choosing what to include and what to leave out
• Making recommendations that are supported by the data

Key Concepts

Raw data doesn't persuade anyone. Neither do spreadsheets. What your boss, your client, or your board wants is a narrative: here's what happened, here's why it matters, and here's what we should do about it.

This lesson teaches you to go from raw numbers to a polished narrative:

1. Start with the "so what?" -- What decision does this data inform? Lead with that.
2. Support with evidence -- Use the specific numbers that back up your point (not all the numbers).
3. Add context -- Comparisons, benchmarks, and trends that help the reader understand scale.
4. End with a recommendation -- Data without a recommendation is just homework for your reader.

Claude will help you practice this with sample data, drafting narratives for different audiences (executive summary vs team update vs client report). You'll iterate on tone, length, and level of detail.

The Module 1 skills are your quality check: make sure your own narrative isn't cherry-picking, isn't confusing correlation with causation, and isn't hiding unfavorable data.

How to Start

Open Claude Desktop and say:

start lesson 2.4

Skills You'll Use Later

• Narrative structure (used every time you present data)
• Audience-aware communication (adapting the same data for different readers)
• Self-editing with AI (iterating until the output is genuinely useful)