Claude for Data / Analytics

Last verified: 13 February 2026 | Applies to: All plans (plugins require Pro or above)

In 30 seconds

The Data plugin turns Claude into an analyst who speaks SQL across dialects, builds visualisations, and creates interactive dashboards. For data leads, it handles the ad hoc requests that interrupt your deep work — “can you pull this?” becomes something the requester can do themselves. For operators without data teams, it’s the analyst you couldn’t afford to hire.

Recommended setup

Component	What to set up	Why
Plan	Pro (solo) or Team (data team)	Full platform access
Data plugin	Install first — SQL, dashboards, statistics	Your primary tool
Productivity plugin	Seed with your data sources, schemas, and terminology	Persistent context
Connectors	Google Sheets, your database (if MCP-compatible)	Live data access

Essential plugins

1. Data — SQL across dialects, visualisations, dashboards, statistical analysis.
2. Productivity — memory of your data landscape, schemas, and business metrics.
3. Finance — for when data analysis overlaps with financial reporting (it often does).

Typical workflows

Ad hoc analysis:

Here's our sales data [upload CSV]. Top 10 customers by revenue, monthly trend, and which product categories are growing fastest.

Dashboard creation:

Build an interactive dashboard: revenue over time, revenue by region, product mix, and KPI cards. Use the data in q1-sales.csv.

Database queries:

Connect to our PostgreSQL database. Show customers with lifetime value over $10K who haven't ordered in 90 days.

Statistical analysis:

Run a correlation analysis between marketing spend and revenue by region. Is it significant?

Data cleaning:

Clean this customer export: deduplicate on email, standardise phone numbers to E.164, fill missing country codes from postcodes, split by region.

Self-service enablement:

Create a CLAUDE.md file for our data folder that explains our schema, key tables, and common queries. So non-technical team members can ask Claude data questions directly.

Time saved

Task	Before Claude	With Claude
Ad hoc data pull	30-60 minutes	5 minutes
Interactive dashboard	1-2 weeks (BI tool)	20 minutes
Data cleaning (1000 records)	2-3 hours	15 minutes
Statistical analysis	1-2 hours	15 minutes

What to watch out for

• SQL queries should be reviewed before running against production databases.
• Statistical analysis outputs should be verified by someone who understands the methodology.
• Dashboard descriptions are conceptual — implementation depends on your BI tool.
• Data cleaning recommendations should be validated against your data dictionary.

Related

• Data Analysis — full analysis workflow
• Data Plugin — complete plugin reference
• Document Creation — turn data into reports
• Product Manager guide — related content for product analytics and metrics
• Finance guide — related content for financial data analysis
• Choosing a Plan — which plan fits your needs
• Security & Privacy — how Claude handles your data

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