Using a supermarket analogy, this article helps healthcare leaders understand what data lakes are (open reservoirs for vast amounts of data), why they’re essential (they reduce the time and resources required to map data), and how they integrate with three common analytic architectures:
- Early-Binding Data Warehouse
- Late-Binding Data Warehouse
- Map-Reduce Hadoop System
Data lakes are useful parts of all three platforms, but deciding which platform to integrate a data lake with depends heavily on a health system’s resources and infrastructure.
Once understood and appropriately integrated with the optimal analytics platform, data lakes save health systems time, money, and resources by adding structure to data only as use cases arise.