Conducting today’s clinical trials requires innovative approaches to managing the exponential increase in the volume and variety of data being collected across the development lifecycle. With the rise of Decentralized Clinical Trials (DCTs) and modern trial approaches comes a new set of challenges that the traditional clinical data warehouses and data lakes are not designed to support. The necessary evolution towards a data Lakehouse architecture eliminates data silos, and increases performance, flexibility, and scalability to better support modern clinical trials while ensuring a solid foundation for the future of digitization. The Lakehouse architecture also supports the use of modern techniques like Artificial Intelligence and Machine Learning (AI/ML) to accelerate Data Science and secondary use of data, beyond the submission pipeline.
This webinar will examine what is driving the need for a digital data fabric and the technology infrastructure required to support clinical trial digitization. Additionally, we’ll share the blueprint for a Unified Clinical Data Lakehouse and discuss how the elluminate® Clinical Data Cloud, built on this blueprint, delivers the Lakehouse promise resulting in faster time to value and decreased cycle times.
What You Will Learn
- The What and Why of the clinical data Lakehouse: What is a Clinical Data Lakehouse and why is it so critical now?
- Benefits of a Data Lakehouse vs. data lake/data warehouse
- The importance of a data fabric to support expanding use cases across the clinical development lifecycle
- How elluminate’s Lakehouse blueprint provides a scalable and unified architecture for seamless data flows and interoperability and facilitates the use of AI/ML in support of Data Sciences disciplines
- Strategic focus areas for further enablement, including embedded AI capabilities, SCE data sciences workbench, and data sharing
Who Should Attend?
- Data Management
- R&D IT
- Clinical Programming
- Data Sciences
- Clinical Operations