Data analysis with Claude Code: queries, CSVs and a weekly digest

What Claude Code does for data analysis

• Answers questions with SQL against a read-only role or replica, and shows the query with the answer.
• Cleans and analyses CSV exports with Python, and draws the charts.
• Writes a weekly metrics digest: what moved, by how much, and the likely reason.
• Flags anomalies, such as a drop in sign-ups or a spike in errors, before someone has to notice.

Claude Code features for data analysis

How to set up Claude Code for data analysis

1. Connect the tools

   Create a read-only database role and give Claude Code that connection, or your warehouse CLI signed in as a read-only user. For one-off analysis, put the CSV exports in the working folder.

   -- Postgres: a read-only role for the agent
   CREATE ROLE analyst LOGIN PASSWORD '<password>';
   GRANT pg_read_all_data TO analyst;

2. Write the rules in CLAUDE.md

   Claude Code reads CLAUDE.md at the start of every session, claude -p runs included. Put the job's rules there, or in a skill under .claude/skills/ if they're long. See the CLAUDE.md guide.

   ## Data rules
   - Read-only: use the analytics role, never the app's database
     user. No INSERT, UPDATE, DELETE or schema changes.
   - Show the query or script behind every number.
   - Compare with the period before, and say when a change is
     within normal noise.
   - Don't export personal data; aggregate before you write
     anything down.
   - Weekly digest: the five numbers that matter, what moved, and
     one question worth asking next week.

3. Run it without the interactive interface

   claude -p runs one task and exits, so cron, CI or another tool can start it. Choose what it may do without asking with --allowedTools or --permission-mode; --output-format json returns the result with its cost.

   # Last week's numbers as JSON for a dashboard or a post
   claude -p "Compute last week's sign-ups, activation and revenue vs the week before" \
     --output-format json --json-schema "$(cat metrics.schema.json)"

4. Put it on a schedule

   Make it a cloud scheduled task with /schedule (Pro, Max, Ultra, Team and Enterprise), a desktop scheduled task, or /loop while a session stays open. See how to make Claude Code proactive.

Source: Claude Code documentation

Limits and safety

• Give it a read-only role. An agent with write access to the database can change it.
• It can misread what a column means. Write a short data dictionary and check its first answers.
• Large results cost context and usage. Query and aggregate before reading rows.
• Since Claude Code v2.1.302, claude -p starts in Manual mode: an action that needs approval is denied unless a rule allows it. Allow only the tools the job needs.

Claude Code or Codex for data analysis?

The rules carry over. Write them once in AGENTS.md and put @AGENTS.md in CLAUDE.md, and both agents read the same file.

Step by step for the other agent: data analysis with Codex.

Make data analysis someone's job

Commands run when someone remembers to run them. Crewmark turns your own Claude Code into an AI employee with a role, a goal in numbers, working hours and a heartbeat, so the work happens on schedule and shows up on a board.

1. Start from the role

   The AI employee roles, with these rules in its brief.

2. Put the work on its board

   Add the job as a recurring issue. The employee wakes on its heartbeat, does it and reports in a comment.

3. Related

   The daily SEO report is a worked example of a recurring analytics job.

FAQ