Bayer Consumer Health, a division of the global life sciences giant, has overhauled its data infrastructure to enable widespread self-service analytics. By adopting Databricks and its Unity Catalog, the company has moved away from fragmented systems and costly data duplication, often referred to as 'data tourism'.
Previously, Bayer's global operations led to isolated data environments across various markets, hindering efficient decision-making. The company struggled with inconsistent data, high management overhead, and difficulties in leveraging advanced analytics like machine learning. This fragmentation meant data often had to be copied multiple times, increasing costs and slowing down innovation.
Consolidating Data Operations
To address these challenges, Bayer Consumer Health sought a unified, scalable, cloud-based data platform. The new architecture, built on Databricks and Azure services, centralizes data transformation and cleansing, ensuring raw data is converted into reliable, reusable assets. This unified approach supports various data roles, from business intelligence reporting to complex machine learning applications.
The implementation of Unity Catalog proved pivotal, providing a centralized governance and metadata layer. This allows for managing core data assets once while enabling secure consumption and reuse across different projects and regions. This streamlined approach to data governance is crucial for managing sensitive information and ensuring data integrity at scale.
Accelerating Analytics and Innovation
With Unity Catalog replacing its previous Hive Metastore, Bayer transitioned to a pull-based data sharing model. Data consumers now access governed core assets, simplifying data access and reducing the need for data replication. This shift has significantly sped up the development and testing of new analytics solutions, as engineers can work with production-grade data in development environments.