Jeremy Deyo

Senior Data Architect at Tango Analytics

From Data Chaos to Cohesion: Unifying Data Warehouses After Rapid Growth

Rapid growth through acquisitions often leaves organizations with a patchwork of data warehouses, pipelines, and platforms—each optimized for a different point in time, but collectively difficult to manage and scale. This session tells the story of navigating that complexity. We’ll examine the challenges of integrating disparate data ecosystems, including conflicting data models, redundant ETL processes, and cross-cloud fragmentation. The discussion will then shift to how Tango Analytics is approaching the problem: defining a unified architecture, rationalizing pipelines, and establishing a foundation for long-term scalability and governance. This session focuses on practical lessons, early-stage decision-making, and what it takes to move from fragmentation toward a cohesive data platform.

Jeremy Deyo is a Senior Data Architect at Tango Analytics with over two decades of experience in data architecture, business intelligence, and data engineering. His expertise includes building and optimizing data warehouses, designing scalable ETL/ELT pipelines, and designing data platforms across AWS and GCP, including technologies such as Amazon Redshift and Google BigQuery. He has recently focused on developing distributed data architectures and is leading an initiative to consolidate multiple data warehouses and pipelines into a unified data platform.