Re-architecting the warehouse behind Ancestry's growth years

8 yrs
building Ancestry's data backbone: ↓ batch
times via modular micro-pipelines: LTV
company-wide forecast model shipped

The challenge

Ancestry's subscription business was scaling fast, and the data warehouse underneath it wasn't: a SQL Server platform and monolithic ETL architecture where batch windows kept growing and every change rippled unpredictably. Executive reporting, marketing analytics, and financial forecasting all depended on it.

How we approached it

1
Led the migration of the enterprise data warehouse from SQL Server to Actian Matrix (MPP), re-modeling for analytical scale.
2
Transitioned the ETL architecture from monolithic jobs to modular micro-pipelines — accelerating development cycles and shrinking batch times.
3
Launched a unified data portal consolidating key business metrics for executive and company-wide consumption.
4
Built the customer Lifetime Value forecast model, giving the business forward revenue visibility per signup.

The outcome

A warehouse and pipeline architecture that kept pace with one of the internet's largest subscription businesses, and metrics infrastructure executives actually trusted. The Kimball-methodology rigor from this era still anchors how we model data today.

→ Start a project

Tell us what's broken. We'll tell you how we'd fix it.

Start with a conversation — thirty minutes, engineers on both ends of the call. If we're not the right team, we'll say so and point you somewhere better.

Start a projectemail us