The Problem: 20+ Data Silos
Our client, a rapidly growing e-commerce company, had data spread across Shopify, Google Analytics, Facebook Ads, Mailchimp, their CRM, and a dozen other tools. Getting a simple answer like 'What's our customer acquisition cost by channel?' required hours of manual spreadsheet work.
Leadership was making decisions based on gut feeling rather than data, and marketing teams couldn't attribute revenue to specific campaigns with any confidence.
Building the Data Pipeline
We designed a modern data stack using Fivetran for automated data extraction, Snowflake as the cloud data warehouse, dbt for data transformation, and Power BI for dashboards.
The ETL pipeline connects to every data source, normalizes schemas, and produces a unified customer view that joins purchase history, marketing touchpoints, support interactions, and product usage data. The entire pipeline runs on a schedule with built-in data quality checks.
The Results
Within 8 weeks, the company went from zero unified analytics to a fully operational data platform. Key outcomes included a single source of truth for all business metrics, real-time dashboards that update every 15 minutes, a 40% improvement in marketing ROI through better attribution, and self-service analytics that empowered every team to answer their own questions.
The automated pipeline replaced 20+ hours per week of manual reporting, freeing the analytics team to focus on strategic insights rather than data wrangling.