Shopify Data Pipeline
Build an analytics stack for your Shopify store - pick your warehouse, payment processor, marketing platform, and more, then follow a step-by-step guide to build a full pipeline with an AI analyst.
What is this? A hands-on tutorial for Shopify store owners and teams. You'll build an analytics pipeline that pulls data from your Shopify store and the tools around it, transforms it into business reports, and sets up an AI data analyst that can run locally, in Bruin Cloud, or connected to your Slack/Teams. You'll also create dashboards and scheduled reports.
What you'll use: Bruin CLI for data extraction, transformation, and pipeline orchestration, your choice of data warehouse, Claude Code with Bruin MCP to help build and test the pipeline, and Bruin Cloud for deployment, dashboards, and team access.
What you'll build: data ingestion from Shopify and your surrounding tools, a staging layer that cleans and joins data across sources, business reports (revenue, cohorts, product performance, marketing ROI), an AI data analyst, and cloud deployment with dashboards.
Who this is for: anyone running a Shopify store - marketing, ops, analytics, or founder. No data engineering experience required. Basic SQL helps but isn't necessary; Claude Code will help you write queries along the way.
Pick your stack, customize the tutorial
Before you start
- Git installed
- Bruin CLI installed
- A data warehouse account (ClickHouse, BigQuery, or Snowflake)
- A Shopify store with API credentials
- API credentials for your selected payment, marketing, ads, and analytics tools
- Claude Code installed (this tutorial uses Claude Code throughout, but you can adapt the prompts for Cursor or Codex)