Data analysts produce the numbers. But they spend a surprising amount of time writing the words. AI handles the writing so you can stay in the analysis.
Analysis narratives and executive summaries. Take your findings and give Claude the context and the data. Ask it to write the executive summary a VP would want: what you found, why it matters, and what the business should do. The analysis is yours; the language is AI-assisted.
SQL and Python drafting. Claude can write competent SQL and Python from a plain-English description. It is not always perfectly optimized, but it is a strong starting point and often saves 30-60 minutes per query for complex joins or transformation logic.
Documentation and data dictionaries. Paste a table schema or a query. Claude documents it: column descriptions, business logic notes, data lineage summaries. Documentation that no analyst wants to write takes 10 minutes instead of never.
Slide and report copy. When your analysis needs to go into a stakeholder presentation, Claude can draft the slide copy, the supporting narrative, and the recommendations section.
For analysis narratives: "Here is the summary of my analysis: [paste findings]. The audience is [describe]. They care most about [business outcome]. Write a 3-paragraph executive summary: (1) the headline finding, (2) the two most important supporting data points, (3) one or two actions the business should take."
For SQL drafting: "Write a SQL query that [describe what you want]. The relevant tables are: [describe schema briefly]. I need to [describe the join or transformation logic]. Output should be grouped by [X] and sorted by [Y]." Expect to edit the output.
Time savings: Analysis narratives: 60-90 minutes to 20-30 minutes. SQL drafting: 30-60% time reduction on novel queries. Documentation: near-zero time for tasks analysts previously deferred indefinitely.
AI-generated SQL and Python can be confidently wrong. Claude will produce code that looks syntactically correct but produces logically incorrect results, especially for edge cases in aggregations or complex join conditions. Always test the output against known data.
Analysis narratives can overstate certainty. Claude writes confidently. If your data shows a weak or ambiguous signal, the AI narrative will often make it sound more definitive than it is.