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# How the FDA is building a secure, AI-ready data foundation on Databricks for Government

**[databricks](https://daily.dev/sources/databricks)** · 7 min read · 0 upvotes · 0 comments

## Summary

The FDA built HALO, an enterprise data platform on Databricks running on AWS GovCloud, to consolidate siloed data and enable secure, governed AI across its regulatory centers. After FedRAMP High authorization, a GovCloud migration, and Unity Catalog adoption, the agency migrated over 5,000 users and 8,000 jobs with zero downtime, refactored more than 1,000 pipelines and 4,000 notebooks, and onboarded eight centers and 30 programs. Reported gains include 30%+ faster BI query response times, 20%+ lower compute costs, 75%+ less time on provisioning and data sharing, and 35%+ lower operational overhead. The platform now integrates with Elsa, FDA's enterprise AI platform, powering initiatives like MARS for regulatory submission review, with a human-in-the-loop approach to AI adoption.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.databricks.com/blog/how-fda-building-secure-ai-ready-data-foundation-databricks-government>

## Questions this post answers

### What operational improvements did the FDA report after migrating to Databricks on AWS GovCloud with Unity Catalog?

Query response times for BI workloads improved by more than 30%, compute costs fell by more than 20%, time spent on provisioning, permissioning, and data sharing dropped by more than 75%, and operational overhead declined by more than 35%. The migration covered over 5,000 users and 8,000 jobs and pipelines with zero downtime, refactoring more than 1,000 pipelines and 4,000 notebooks.

_daily.dev surfaces real-world case studies for teams weighing large-scale data platform migrations._

### What is HALO in the context of the FDA's data platform?

HALO stands for Harmonized AI and Lifecycle Operations for Data, the FDA's enterprise data platform built on Databricks running on AWS GovCloud. It serves as a secure, governed, AI-ready foundation used by multiple regulatory centers under a multi-tenant architecture, where centers share common infrastructure but retain their own governed spaces and access policies.

_engineers researching federal data platform architecture can follow similar deep dives on daily.dev._

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---

Tags: [#aws](https://daily.dev/tags/aws), [#big-data](https://daily.dev/tags/big-data), [#databricks](https://daily.dev/tags/databricks), [#unity-catalog](https://daily.dev/tags/unity-catalog)

[View this post on daily.dev](https://daily.dev/posts/how-the-fda-is-building-a-secure-ai-ready-data-foundation-on-databricks-for-government-ttx4nsvrc)

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