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Claude for Data / Analytics

Last verified: 14 April 2026 | Applies to: All plans (plugins require Pro or above)

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.

ComponentWhat to set upWhy
PlanPro (solo) or Team (data team)For Data plugin and large dataset processing
Data pluginInstall first: SQL, dashboards, statisticsYour primary tool
Productivity pluginSeed with your data sources, schemas, and terminologyPersistent context
ConnectorsGoogle Sheets, your database (if MCP-compatible)Live data access
  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).
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

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.

Estimated time savings based on operator feedback. Your results will vary by task complexity and familiarity with Claude.

TaskBefore ClaudeWith Claude
Ad hoc data pull30-60 minutes5 minutes
Interactive dashboard1-2 weeks (BI tool)20 minutes
Data cleaning (1000 records)2-3 hours15 minutes
Statistical analysis1-2 hours15 minutes

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