Best Claude Prompts for Data Analysis (2026)

You are a senior data analyst. I have a dataset about [describe data and columns] and this question: [your question]. Propose an exploratory analysis plan: what to check first, which relationships to test, what could mislead me, and the order to do it in. Do not write code yet, just the plan and your reasoning.

Write a SQL query for [database type] that answers: [describe precisely]. Here is the relevant schema: [paste tables and columns]. Show the query, explain each part, and note any assumptions about the data. Flag edge cases like nulls or duplicates that could change the result.

Here are my analysis results: [paste numbers or output]. Explain what they actually mean in plain language, what they do not mean, and how confident I should be. Point out any way these numbers could be misread.

Review this data sample and summary stats: [paste]. List likely data quality issues such as outliers, missing values, inconsistent formats, suspicious distributions, or duplicates. For each, explain the risk and how I would check it. Be skeptical.

Summarize this analysis for a non-technical stakeholder: [paste findings]. Lead with the single most important takeaway, give 2 to 3 supporting points in plain language, state the main caveat, and recommend a next step. No jargon, no charts described in detail.

I want to measure [goal, e.g. user engagement]. Suggest 3 candidate metrics, explain what each captures and misses, warn me about ways each could be gamed or misleading, and recommend one with your reasoning. Context: [paste].

I am about to conclude [claim] based on [describe the analysis and data]. Play skeptic. What assumptions am I making, what could explain this result besides my hypothesis, is the sample adequate, and what would change your mind? Be direct.

Here is a data table: [paste]. Identify the 3 most interesting patterns, the most surprising thing in it, and one finding that is probably noise rather than signal. Explain how you would verify each before trusting it.

A stakeholder asked: '[their vague question]'. Help me turn this into a concrete analysis: clarify what they likely want to know, list the questions I should ask them, define the metrics and data needed, and outline the steps to answer it.

Explain what this analysis code does at three levels: a one-sentence summary, a paragraph for a colleague, and a walkthrough of the tricky transformations. Note any assumptions or steps that could introduce bias. Code: [paste].