Case study
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2 min read

From fragmented to unified

By Zenitech,
on 2nd április 2026

Zenitech helped an entertainment company consolidate fragmented partner data infrastructure into Snowflake, using a two-workstream strategy and a compatibility layer to migrate without disrupting clients. Critical systems like DOMO ran in parallel for validation, and the team left with full internal capability to manage the new platform.

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Industry
Entertainment & Media
Services
Átalakítás
Technologies
DevOps Full Stack

Giving Marketing back control

An entertainment company’s Partner Data Engineering team, spread across London and Los Angeles, managed partner data scattered across multiple applications. What began as isolated solutions had evolved into complex, fragmented infrastructure. The vision was clear, consolidate into Snowflake, but execution proved far more intricate than a simple lift-and-shift: multiple clients had built dependencies on the existing Athena infrastructure, the Partners Eventing Platform operated in real time, and partner services including Authorisation, Product, and Disclosure each presented unique challenges. Zenitech augmented the team with specialist data and analytics engineers.

Rather than risk a big-bang migration, the customer and Zenitech designed a two-workstream strategy. The first systematically onboarded partner data into Snowflake, starting with Unity data to establish proven patterns before progressively bringing in the Partners Eventing Platform, DevNet extensions, GEMS, TMDB, and ASM systems. The second workstream tackled Athena decommissioning by building a sophisticated compatibility layer; a translation mechanism letting client systems keep functioning as before while drawing from Snowflake instead of Athena, covering Content Pipeline, PMDB, Okta, and RoleService.

DOMO, critical for business reporting, received special treatment: the team ran legacy and new datasets in parallel, letting business users validate identical results before retiring legacy datasets, so critical BI operations ran uninterrupted throughout.

The compatibility layer proved transformative, clients continued operating seamlessly, often unaware they were now drawing from Snowflake. Daily collaboration also enabled genuine knowledge transfer, leaving the customer’s internal teams fully equipped to manage and evolve the platform independently. The consolidation improved data freshness, positioned the organisation for advanced analytics and machine learning, and made onboarding future data sources far simpler.

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