Amgen is advancing its Enterprise Data Fabric to securely manage sensitive multimodal data, such as imaging and research data, across formats.Databricks is already the de facto standard for governance on structured data, and Amgen seeks to extend it for unstructured multi modal data too. This approach will also allow Amgen to standardize its GenAI projects on Databricks. Key priorities include: Centralized data access: establishing a unified, secure access control system Enhanced traceability: implementing detailed processes for transparency and accountability Consistent access standards: ensuring uniform data access privilege experience User support: providing flexible access for diverse stakeholders Comprehensive auditing: enabling thorough permission audits and data usage tracking Learn strategies for implementing a comprehensive multimodal data governance framework using Databricks, as we share our experience on standardizing data governance for GenAI use cases.

Amgen has invested in building modern, cloud-native enterprise data and analytics platforms over the past few years with a focus on tech rationalization, data democratization, overall user experience, increase reusability, and cost-effectiveness. One of these platforms is our Enterprise Data Fabric which focuses on pulling in data across functions and providing capabilities to integrate and connect the data and govern access. For a while, we have been trying to set up robust data governance capabilities which are simple, yet easy to manage through Databricks. There were a few tools in the market that solved a few immediate needs, but none solved the problem holistically. For use cases like maintaining governance on highly restricted data domains like Finance and HR, a long-term solution native to Databricks and addressing the below limitations was deemed important:

The way these tools were set up, allowed the overriding of a few security policies

• Tools were not UpToDate with the latest DBR runtime
• Complexity of implementing fine-grained security
• Policy management – AWS IAM + In tool policies

To address these challenges, and for large-scale enterprise adoption of our governance capability, we started working on UC integration with our governance processes. With an aim to realize the following tech benefits:

• Independent of Databricks runtime
• Easy fine-grained access control
• Eliminated management of IAM roles
• Dynamic access control using UC and dynamic views

Today, using UC, we have to implement fine-grained access control & governance for the restricted data of Amgen. We are in the process of devising a realistic migration & change management strategy across the enterprise.

Talk by: Lakhan Prajapati and Jaison Dominic

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