Bruin Academy

Build a Local AI Data Analyst for the Stock Market

Create an AI data analyst for stock and financial data using Claude Code, Bruin CLI and BigQuery - all running locally on your machine.

Overview

Goal - Create an AI data analyst for stock and financial data using Claude Code, Bruin CLI and BigQuery.

Audience - Data professionals, hobbyists, and financial analysts who want to build a local AI analyst.

Prerequisites

  • BigQuery project and dataset with data already loaded
  • gcloud CLI installed
  • Bruin CLI installed
  • Claude Code installed
  • Bruin MCP added to Claude Code (setup video)

High-level flow

  1. bruin init empty and remove the default SQL asset.
  2. Authenticate to BigQuery with gcloud.
  3. Add and test a BigQuery connection in Bruin.
  4. Import database metadata to create source assets.
  5. Enhance metadata with bruin ai enhance.
  6. Ask a real analysis question.

Steps

1) Initialize pipeline

  • Run bruin init empty sp500 or select the empty template and name the folder sp500.
  • Remove the placeholder asset or any other empty placeholder files (e.g. rm sp500/assets/empty.sql)

2) Authenticate to BigQuery

  • Run gcloud auth login.

3) Add and test a BigQuery connection

  • List existing connections: bruin connections list.
  • Add a new connection: bruin connections add.
    • Set environment: default.
    • Set name: gcp-default.
    • Choose google_cloud_platform connection and provide credentials. See BigQuery connection options.
    • Provide a service account file, or set use_application_default_credentials to true to use gcloud auth login.
    • If prompted to set as default, answer true.
  • Test the connection: bruin connections test --name gcp-default --env default.

4) Import database metadata

  • Run bruin import database sp500 --connection gcp-default --schema stock_market.

5) Enhance asset metadata

  • Run bruin ai enhance sp500/ using Claude Code.

6) Ask the analysis question

  • Prompt: "Which companies had their free cash flow margin improve in the past 4 quarters but saw their stock price decrease more than 10% during the same period?"
  • Ensure the agent uses bruin query for data access and returns a table or chart.

Sample outputs

  • The analysis prompt and a summary of results.
  • A simple table or chart output.

Troubleshooting

  • Common BigQuery permission issues.
  • Bruin connection errors or missing credentials.
  • AI CLI authentication errors for bruin ai enhance.

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