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The Insight Engine

The AI agent is your intelligent assistant for data analysis. Ask questions in plain English and watch as it builds complete analysis workflows automatically.

How It Works​

The Insight Engine appears in the right sidebar of any notebook. It can:

  • Write SQL queries from natural language descriptions
  • Create and execute cells to answer your questions
  • Build multi-step analyses with proper cell dependencies
  • Understand your data through schema introspection
  • Use semantic definitions for accurate, consistent metrics

Starting a Conversation​

  1. Open any notebook
  2. Click the chat icon in the right sidebar
  3. Type your question and press Enter

Example questions:

  • "Show me the top 10 customers by revenue"
  • "What's the month-over-month growth rate?"
  • "Create a chart showing sales by region"
  • "Join users with orders and find the average order value"

Tool Approvals​

For sensitive operations, the agent asks for your approval before executing. You'll see a summary of what it wants to do:

  • Creating cells — Shows the SQL or content to be added
  • Executing queries — Shows which cells will run
  • Modifying structure — Shows proposed changes

Click Approve to proceed or Reject to cancel.

Conversation Management​

You can have multiple conversations per notebook:

  • New conversation — Start fresh context
  • Rename — Give conversations meaningful names
  • Delete — Remove old conversations

Each conversation maintains its own context and history.

Grounding with Semantic Layers​

The agent becomes more accurate when you define semantic layers. These provide:

  • Metric definitions — How to calculate revenue, churn, etc.
  • Dimension mappings — How to group and filter data
  • Join paths — How tables relate to each other
  • Business context — What terms mean in your domain

Best Practices​

Be Specific​

Instead of "show me sales", try "show monthly sales revenue for 2024, grouped by product category"

Iterate​

Start with simple questions, then ask follow-ups to drill deeper

Use Your Schema​

Reference actual table and column names when you know them

Define Metrics​

Create semantic layers for metrics you use frequently

Agent Studio​

Monitor your AI usage in Agent Studio:

  • Total conversations
  • Usage by team member
  • Cache efficiency (how often cached responses are reused)
  • Conversation search

This helps optimize costs and understand how your team uses the AI.

Limitations​

  • The agent works best with well-structured schemas
  • Very complex queries may need manual refinement
  • Large result sets are sampled for display
  • Some operations require tool approval