Labcorp Data Platform Journey: From Selection to Go-Live in Six Months

Labcorp Data Platform Journey: From Selection to Go-Live in Six Months

Join this session to gain insights into Labcorp’s successful transformation of their data platform, transitioning from an on-premises Hadoop environment to AWS Databricks Lakehouse. Labcorp will share valuable best practices and lessons learned throughout the cloud-native data platform selection, implementation, and migration process, which was accomplished within a remarkable six-month timeframe. Unity Catalog played a crucial role in this transformation.

The session will outline the steps Labcorp took to retire various legacy on-premises technologies and effectively utilize Databricks’ native features. These features include Spark streaming, workflows, job pools, cluster policies, and Spark JDBC within the Databricks platform. Labcorp will share valuable insights and lessons learned in implementing Unity Catalog, which facilitated the establishment of a robust security and governance model capable of scaling across applications. Demonstrations will showcase the batch frameworks, streaming frameworks, and data compare tools utilized across multiple applications to enhance data quality and expedite delivery.

Attendees will discover how Labcorp achieved operational efficiency, improved resiliency, and reduced total cost of ownership (TCO) through this transformation. Additionally, Labcorp will discuss the scalability of building workspaces and associated cloud infrastructure using the Terraform provider, offering practical insights for organizations seeking to scale their data infrastructure effectively.

In summary, this session offers a unique opportunity to learn from Labcorp’s successful journey in migrating from on-premises Hadoop to AWS Databricks Lakehouse. By sharing best practices, lessons learned, and demonstrating the benefits achieved, Labcorp aims to inspire and guide organizations in their own data platform transformations, ultimately improving operational efficiency, data quality, and scalability.

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