When to use the Data Analyst Agent
The Data Analyst Agent is ideal when you need to:- Query databases: Write and execute SQL queries against your connected data sources
- Analyze data: Explore patterns, calculate metrics, and investigate trends in your data
- Create visualizations: Generate professional charts and graphs using seaborn
- Answer data questions: Get quick, accurate answers to questions about your data
- Generate insights: Discover patterns, anomalies, and actionable findings
Accessing the Data Analyst Agent
From the web app
- Go to the Devin home page
- Click the agent picker dropdown
- Select Data Analyst from the dropdown menu
- Start your session with a data-related question or task
From Slack
You can start a Data Analyst session directly from Slack using either method: Using the slash command:!dana macro:
Prerequisites
Before using the Data Analyst Agent, you’ll need to connect at least one data source via MCP (Model Context Protocol). Common integrations include:- Database MCPs: Redshift, PostgreSQL, Snowflake, BigQuery, and other SQL databases
- Analytics MCPs: Datadog, Metabase, and other observability platforms
Set up MCP integrations
Learn how to connect databases and other data sources via MCP
How it works
Database Knowledge
The Data Analyst Agent maintains a Database Knowledge note that contains schema documentation for your connected databases. This knowledge is automatically referenced before running queries, allowing the agent to quickly identify the right tables and columns.Example prompts
Here are some effective ways to use the Data Analyst Agent: Simple questions:- “How many active users did we have last week?”
- “What’s our daily revenue trend for the past month?”
- “Which customers have the highest usage?”
- “Analyze user retention by cohort for Q4”
- “Break down consumption by enterprise vs. self-serve customers”
- “Find the top 10 users by session count and show their activity over time”
- “Why did signups drop last Tuesday?”
- “Are there any anomalies in our error rates this week?”
- “Compare this month’s metrics to the same period last year”
Best practices
Be specific about metrics
Instead of asking vague questions, be specific about what you want to measure:Specify time periods
Always include the time period you’re interested in:Ask for visualizations
Request charts when they would help communicate the data:Validate the SQL
The agent always includes the SQL query it used. Review it to ensure the logic matches your expectations, especially for complex analyses involving joins, filters, or aggregations.Knowledge management
The Data Analyst Agent can persist learnings across sessions using the knowledge system. When it discovers:- New schema information or table relationships
- Business logic or metric definitions
- Data quality patterns or caveats
Learn more about Knowledge
Understand how Devin’s knowledge system works
Differences from standard Devin
| Capability | Data Analyst Agent | Standard Devin |
|---|---|---|
| SQL query execution | Optimized | Supported |
| Data visualizations | Built-in seaborn support | Manual setup |
| Database schema awareness | Pre-loaded knowledge | On-demand exploration |
| Response style | Concise, metrics-focused | Detailed explanations |
| Code changes | Not primary focus | Full support |
| MCP integrations | Required | Optional |