Starter prompts for data analysis
Copy a prompt, replace the [BRACKETS], and paste it into the bot your organization allows. Each one tells the bot what not to do, so it is easier to check.
1. SQL from schema
Schema: [CREATE TABLE statements]. Write a SQL query that answers: [QUESTION]. Use CTEs, comment each step, and state assumptions about NULLs and duplicates.2. Validated pandas
Write a pandas script to [TASK]. After each step, add an assert or print that checks row count, nulls and duplicate keys. Do not drop rows silently.3. Summary from results
Write a 5-bullet executive summary of this result table. Quote each number exactly and say "not significant" or "no test run" where appropriate. Do not claim causes.
[TABLE]Before you paste: remove names, account numbers, dates of birth, addresses and anything else that identifies a real person, unless the tool is approved for that data.
Accuracy and ethics, every time
- Confidentiality: never paste client, patient, student, employee or customer personal data (PII/PHI) into a public bot. Use tools your organization has approved, with contract terms that cover data use, or remove identifiers first.
- Verify everything: bots can invent citations, case law, statistics, doses, code sections and quotes that look real. Check each one against the original source before you rely on it.
- Not professional advice: these tutorials teach you how to use AI tools. They are not legal, medical, tax, financial or engineering advice.
- A human professional is responsible: the licensed or accountable person reviews, decides and signs. The bot drafts; you own the result.
- Prices change: we don't list product prices. Check each vendor's official pricing page.
Official sources for this section
- NIST AI Risk Management Framework: AI risk
- NIST/SEMATECH e-Handbook of Statistical Methods: free statistics reference
- Data.gov: public datasets for practice
Links checked Oct 30, 2026. Rules differ by state and country; follow your licensing body and employer policy.
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