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Blog/Prompts for Claude AI Data Analysis: 30 Free Templates [2026]
Data & Analysis7 min read•Updated Feb 2026

Prompts for Claude AI Data Analysis: 30 Free Templates

Copy-paste prompts for Claude AI to analyze spreadsheets, write SQL, spot trends, and turn raw numbers into executive summaries.

Spreadsheets & CSV•SQL & databases•Trends & anomalies
Speed up your analysis workflow
Summarize findings and share results faster.
Meeting Summary Generator →Technical Jargon Simplifier →Blog Post Outline (publish findings) →
Summarize a spreadsheet
Analyze this {{format}} data and summarize the key findings in 5 bullet points. Include totals, averages, and any outliers.

Data:
{{data}}
Spot trends over time
Identify the top 3 trends in this time-series data. For each trend, state the direction, magnitude, and likely cause.

Data:
{{data}}
Write a SQL query
Write a SQL query for {{database}} that {{goal}}. Include comments explaining each clause. Tables and columns:
{{schema}}
Clean messy data
Suggest a step-by-step data cleaning plan for this dataset. Flag missing values, duplicates, inconsistent formats, and outliers. Propose fixes for each.

Sample rows:
{{data}}
Build a pivot summary
Create a pivot table summary of this data grouped by {{dimension}}. Show count, sum, and average for {{metric}}. Output as a markdown table.

Data:
{{data}}
Compare two datasets
Compare Dataset A and Dataset B below. List differences in structure, coverage, and values. Highlight mismatches and missing records.

Dataset A:
{{dataset_a}}

Dataset B:
{{dataset_b}}
Generate chart recommendations
Recommend 3 chart types for visualizing this data. For each, explain why it fits, what to put on each axis, and one insight it would reveal.

Data description:
{{description}}
Executive summary from raw numbers
Turn this raw data into a 3-paragraph executive summary for {{audience}}. Lead with the headline number, explain context, and end with a recommendation.

Data:
{{data}}
Regression analysis prompt
Analyze the relationship between {{independent_var}} and {{dependent_var}} in this data. Describe correlation direction, strength, and any confounding factors.

Data:
{{data}}
Anomaly detection
Scan this dataset for anomalies. Flag any values that are statistical outliers (>2 SD from mean) or logically inconsistent. Explain why each is suspicious.

Data:
{{data}}

Tips for data prompts

  • Always include column headers so Claude understands the schema.
  • Specify your SQL dialect (PostgreSQL, MySQL, BigQuery) for accurate syntax.
  • Ask for markdown tables or JSON to get structured, copy-paste-ready output.
  • For large datasets, paste a sample and describe the full shape (rows, columns, date range).

FAQ

Can Claude analyze large spreadsheets?
Claude handles up to ~100K tokens of context. For very large files, paste the first 200 rows or summarize the schema and ask Claude to write analysis code.
Should I paste raw CSV or describe the data?
For small datasets (<50 rows), paste directly. For larger ones, paste the header + 10 sample rows and describe the full dataset shape.
Is Claude good at SQL?
Yes. Claude excels at SQL across PostgreSQL, MySQL, BigQuery, and SQLite. Always include your schema and specify the dialect.
How do I get consistent output formats?
Ask for markdown tables, JSON, or CSV explicitly. Add "Output as a markdown table with headers" to your prompt.

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