Claude for Data / Analytics
Last verified: 14 April 2026 | Applies to: All plans (plugins require Pro or above)
In 30 seconds
Section titled “In 30 seconds”Half your week disappears into ad hoc requests that could answer themselves. “Can you pull this number?” “Can you build me a quick chart?” The Data plugin turns Claude into an analyst who speaks SQL across dialects, builds visualisations, and creates interactive dashboards. For data leads, it deflects the interruptions. For operators without data teams, it is the analyst you could not afford to hire.
Recommended setup
Section titled “Recommended setup”| Component | What to set up | Why |
|---|---|---|
| Plan | Pro (solo) or Team (data team) | For Data plugin and large dataset processing |
| 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
Section titled “Essential plugins”- Data: SQL across dialects, visualisations, dashboards, statistical analysis.
- Productivity: memory of your data landscape, schemas, and business metrics.
- Finance: for when data analysis overlaps with financial reporting (it often does).
Your workflow map
Section titled “Your workflow map”graph LR
Request[Ad hoc request] --> Ingest[Upload or connect data]
Ingest --> Clean[Clean and validate]
Clean --> Analyse[SQL / statistics]
Analyse --> Viz[Visualisation]
Analyse --> Dashboard[Interactive dashboard]
Viz --> Share[Share with stakeholders]
Dashboard --> Share
Share --> Iterate[Refine and iterate]
Iterate --> Analyse
Typical workflows
Section titled “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
Section titled “Time saved”Estimated time savings based on operator feedback. Your results will vary by task complexity and familiarity with Claude.
| 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 |
Recommended workflows
Section titled “Recommended workflows”Related
Section titled “Related”- Data Plugin: complete plugin reference
- 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
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