Case Study: CBC/Radio‑Canada achieves 50% faster time-to-insight and scalable personalization with the Databricks Lakehouse Platform

Reimagining public broadcasting with personalization

CBC/Radio‑Canada, Canada’s public broadcaster, needed to personalize services across a vast and diverse audience but was hampered by fragmented data and a costly, inflexible Hadoop stack. Teams struggled to access and analyze high‑volume audience, device and content signals, which slowed insight generation and limited their ability to drive engagement and retention.

By migrating to the Databricks Lakehouse on Azure and using Databricks SQL and Delta Lake, CBC/Radio‑Canada unified its data, sped up pipeline and dashboard workflows, and improved data reliability with ACID transactions. The move cut time to insight from weeks to minutes (about a 50% reduction reported), lowered operational costs, boosted analyst trust and freed the team to focus on personalization strategies that increase engagement and retention.

CBC/Radio-Canada

Stephane Caron

Sr. Director of Business Intelligence