Do you know a single patient produces approximately 80 megabytes of medical data every year? Multiply that across thousands of patients over their lifetime, and you’re looking at petabytes of patient data that contains valuable insights. Unlocking these insights can help streamline clinical operations, accelerate drug R&D and improve patient health outcomes. But first, the data needs to be prepared for downstream analytics and AI. Unfortunately, most healthcare and life sciences organizations spend an inordinate amount of time simply gathering, cleaning and structuring their data.
Here are the classic 4V challenges of big data in Health Care Eco System
CHALLENGE #1: VOLUME : Scaling for rapidly growing health data
CHALLENGE #2: VARIETY : Analyzing diverse health data
CHALLENGE #3: VELOCITY : Processing streaming data for real-time patient insights
CHALLENGE #:4 VERACITY : Building trust in healthcare data and AI
The lakehouse architecture helps healthcare and life sciences organizations overcome these challenges with a modern data architecture that combines the low cost, scalability and flexibility of a cloud data lake with the performance and governance of a data warehouse. With a lakehouse, organizations can store all types of data and power all types of analytics and ML in an open environment.
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