---
title: "NBCUniversal’s Seamless Migration: Unlocking Scalable Analytics with Databricks"
description: "NBCUniversal sought to modernize its data infrastructure as growing data volumes, evolving analytics demands, and slot-based compute reservations created cost, contention, and flexibility concerns. Working with EXL and Databricks, it migrated workloads to a Databricks lakehouse architecture that unifies data engineering, analytics, machine learning, and business intelligence. The phased, risk-based program assessed workloads and dependencies, designed workspaces and governance with Unity Catalog, and used four custom accelerators for SQL translation, DAG migration, data transfer, and validation. Job-specific compute, autoscaling, Delta Lake layouts, MLflow, and Lakeflow Jobs supported workload-specific execution and operations. The reported outcome was a 30% reduction in data infrastructure costs, elastic scaling for high-traffic events, unified ML operations, and the onboarding of approximately 300 analysts to Databricks SQL."
---

# NBCUniversal’s Seamless Migration: Unlocking Scalable Analytics with Databricks

[Databricks](https://yomu.fyi/company/databricks) · Kevin Hill, Ludwig Kuznia, Anil Joshi, Jay Mehta, Manojit Dan · Jul 29, 2026

**Type:** Problem & solution

## Summary

NBCUniversal sought to modernize its data infrastructure as growing data volumes, evolving analytics demands, and slot-based compute reservations created cost, contention, and flexibility concerns. Working with EXL and Databricks, it migrated workloads to a Databricks lakehouse architecture that unifies data engineering, analytics, machine learning, and business intelligence. The phased, risk-based program assessed workloads and dependencies, designed workspaces and governance with Unity Catalog, and used four custom accelerators for SQL translation, DAG migration, data transfer, and validation. Job-specific compute, autoscaling, Delta Lake layouts, MLflow, and Lakeflow Jobs supported workload-specific execution and operations. The reported outcome was a 30% reduction in data infrastructure costs, elastic scaling for high-traffic events, unified ML operations, and the onboarding of approximately 300 analysts to Databricks SQL.

## Context

NBCUniversal’s existing infrastructure faced growing data volumes, increasingly complex queries and workloads, compute costs from slot reservations, resource contention, and limited flexibility for advanced analytics and machine learning. The company also wanted to scale for major content launches, awards shows, and live events without overprovisioning.

## Approach / What changed

NBCUniversal partnered with EXL and Databricks on a phased migration. The work covered landscape assessment, target architecture design, Unity Catalog governance, workload-specific job clusters, Delta Lake storage optimization, a representative MVP, and migration waves supported by custom tools for SQL conversion, DAG recreation, data transfer, and validation.

## Takeaways

- The migration replaced shared slot reservations with dedicated job-specific compute, allowing pipelines to scale independently and reduce waste during lower-demand periods.
- EXL created four migration accelerators: a SQL translation engine, an orchestration migrator, a data transfer orchestrator, and a validation framework comparing results, row counts, and aggregates.
- Databricks SQL’s ANSI SQL compliance and unified workspace enabled approximately 300 analysts to transition, while MLflow and Lakeflow Jobs supported model operations and workflow standardization.

**Tags:** [Architecture](https://yomu.fyi/topic/architecture), [Databricks](https://yomu.fyi/topic/databricks), [Data Pipelines](https://yomu.fyi/topic/data-pipelines), [Machine Learning](https://yomu.fyi/topic/machine-learning)

- Source: [Databricks](https://www.databricks.com/blog/nbcuniversals-seamless-migration-unlocking-scalable-analytics-databricks)
- Source URL: https://www.databricks.com/blog/nbcuniversals-seamless-migration-unlocking-scalable-analytics-databricks
- Ingested by Yomu: 2026-08-30T16:52:36.568Z

[Read original post](https://www.databricks.com/blog/nbcuniversals-seamless-migration-unlocking-scalable-analytics-databricks)