How do biopharma companies build a unified data lakehouse for R&D and commercial data?

Summary

• Biopharma companies unify R&D and commercial data on the Databricks Data Intelligence Platform, a single lakehouse that stores structured and unstructured data in open formats in cloud storage and serves warehousing, ETL, real-time analytics, data science, and AI from one governed copy. See the Data Intelligence Platform.
• Delta Lake provides the open, reliable foundation: an open-source storage layer with ACID transactions that keeps data in open formats, so research and commercial teams work from consistent, trustworthy data. See the Delta Lake documentation.
• Unity Catalog governs research and commercial domains together with a single permission model, fine-grained row- and column-level access, and end-to-end lineage that supports reproducibility and regulatory needs. See Unity Catalog.
• All data modalities live on one platform — genomics and other omics, clinical and trial systems, real-world evidence, and commercial data such as CRM, sales, and claims — supporting FAIR (Findable, Accessible, Interoperable, Reusable) data practices.
• AI and analytics run in place: Mosaic AI, Databricks SQL, streaming pipelines, and Clean Rooms for secure collaboration all operate on the same governed data. See Databricks for Life Sciences.

How do biopharma companies build a unified data lakehouse for R&D and commercial data?

Biopharma organizations often keep research and commercial data in separate systems, which makes it hard to move from discovery insight to commercial impact on one governed foundation. On the Databricks Data Intelligence Platform, R&D and commercial data are brought together in a single lakehouse: all data — structured and unstructured — is stored in open formats in low-cost cloud storage, governed by Unity Catalog, and made available to warehousing, ETL, real-time analytics, data science, and AI without copying it into separate systems. See the Data Intelligence Platform.

Why Databricks for a unified biopharma lakehouse

• One open foundation for all data. The lakehouse combines the scale of a data lake with the reliability and performance of a data warehouse. Delta Lake, an open-source storage layer, provides ACID transactions and keeps data in open formats so teams work from a single, trustworthy copy across SQL, ML, and streaming workloads. See the Delta Lake documentation.
• Governance across research and commercial domains. Unity Catalog provides one permission and cataloging model spanning research and commercial data, with fine-grained row- and column-level access controls and end-to-end lineage that supports reproducibility and regulatory submissions. See Unity Catalog and the Unity Catalog documentation.
• All data modalities together. The platform handles genomics and other omics data, clinical and trial systems (such as electronic lab notebooks, CTMS, LIMS, and imaging), real-world evidence from claims and device data, and commercial data such as CRM, sales, and claims — structured, semi-structured, and unstructured alike. This supports FAIR (Findable, Accessible, Interoperable, Reusable) data-management practices for scientific collaboration and reuse. See the omics data management blog.
• AI and analytics run on the governed data. Mosaic AI supports building models and research and commercial applications on the same platform, Databricks SQL enables analysis and dashboarding of research, clinical, and commercial data, and streaming pipelines support real-time analytics and data-quality checks.
• Secure collaboration. Clean Rooms enable secure data collaboration across partners — for example clinical trial sponsors, sites, and commercial partners — without moving or exposing the underlying data.

Getting started

• Explore Databricks for Life Sciences for industry solutions.
• Read how the platform unifies data warehousing and data lakes in data lakes vs. data warehouses.
• Set up governance across domains with the Unity Catalog documentation.
• Build the open data foundation with the Delta Lake documentation.

FAQs

What is a unified data lakehouse for biopharma?

It is a single platform that stores R&D and commercial data in open formats in cloud storage and serves warehousing, analytics, data science, and AI from one governed copy. On Databricks this is the Data Intelligence Platform, built on Delta Lake and governed by Unity Catalog.

How does a lakehouse bring R&D and commercial data together?

Both research data (genomics, clinical, real-world evidence) and commercial data (CRM, sales, claims) are stored in open formats and governed by one Unity Catalog permission model, so teams can analyze across domains without maintaining separate systems.

How is sensitive research and commercial data governed?

Unity Catalog applies a single governance model with fine-grained row- and column-level access controls and end-to-end lineage, supporting reproducibility, auditability, and regulatory needs across clinical, safety, and commercial environments.

Can biopharma teams run AI on the same platform?

Yes. Mosaic AI, Databricks SQL, and streaming pipelines all run on the same governed lakehouse data, and Clean Rooms enable secure collaboration with external partners.