For decades, healthcare data scientists have focused their efforts mostly on analyzing structured data, typically stored in an enterprise data warehouse where it is cleansed and normalized. But payers and other healthcare stakeholders are increasingly realizing the value of raw data—for instance, consumer financial data or physician notes—and are turning to a data lake architecture to make it readily available to their data scientists alongside structured data.
With the excitement around data lakes continuing to build, I look forward to 
at the 2019 Health Datapalooza coming up March 27 and 28 in Washington, D.C., where I’ll be joined by an expert panel to discuss how a data lake infrastructure enables high-impact data science for improved health. Our panel will include:
- Ian Blunt, director of predictive analytics and data science, Highmark Health
- Heather Cartwright, general manager, Microsoft Healthcare
- Tom Morley, manager of analytics and data strategy, Excellus BlueCross BlueShield of New York
We’ll discuss questions including how a health plan knows that it needs a data lake versus a data warehouse, the role of business and operations leaders in building the lake, and what considerations are most important in selecting a data lake partner. Cotiviti will also be on hand at booth #32 if you'd like to stop by.
Of course, while the enthusiasm for data lakes is real, actually building, implementing, and managing a data lake is no small task. I invite you to read my recent white paper offering seven major considerations for healthcare payers considering a data lake approach, as well as an examination of the root causes of data lake failure.
I hope to see you at Health Datapalooza!
