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Data Analysis With AI Assistants

Using language models to write queries, analyse data and create charts — and checking their work.

Editorial team 1 min read

AI assistants can speed up data analysis considerably, from writing SQL to explaining results.

Useful Tasks

  • Writing and explaining SQL queries.
  • Generating pandas or R code.
  • Suggesting analyses and charts.
  • Cleaning and reshaping data.
  • Summarising findings in plain language.
  • Explaining statistical methods.

Code Execution

Assistants that run code on your data can analyse files directly. This is more reliable than asking a model to calculate in text.

Provide Context

Share table schemas, column meanings, business definitions and sample rows. Ambiguous definitions — what counts as an "active user"? — cause wrong answers.

Check the Work

  • Review generated queries for logic errors, especially joins and filters.
  • Validate results against known figures.
  • Watch for silently dropped rows and double counting.
  • Question surprising results.

Data Protection

Don't upload sensitive data to unapproved tools. Use approved environments or share schemas without data.

Analyst Judgement

Assistants accelerate mechanics; framing questions and interpreting results remain human responsibilities.

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