E-commerce Data Warehouse

Overview

An ecommerce data warehouse centralizes data from your store, ad platforms, shipping carriers, and accounting system into a single analytics layer — enabling reports that no single platform can produce on its own. Most merchants start needing a warehouse when they outgrow their platform's built-in analytics (typically around $1M+ ARR or when managing multiple channels), want to combine ad spend with order data for true ROAS, or need SQL-level access to run custom cohort and attribution analyses.

This skill guides you through extracting data from your platform, loading it into BigQuery (recommended for cost), and transforming it with dbt so your team can build dashboards in Looker Studio, Metabase, or Tableau.

When to Use This Skill

• When your platform's built-in analytics cannot answer important business questions
• When you need to combine data from multiple sources (Shopify + Meta Ads + Google Ads + shipping)
• When you want to build custom cohort retention, LTV, and attribution models
• When analysts or data scientists need SQL access to raw order data
• When you need a single source of truth across multiple sales channels

Core Instructions

Step 1: Choose your warehouse and set up the infrastructure