Many large companies today have invested in some form of data lake to get value from them in the form of real-time analytics. Unfortunately, that promise has failed to materialize. As a result, most data lake owners have discovered that while their investments are very effective for storing vast amounts of raw data, most fall short for meeting the main requirement for doing real-time, large-scale analytics.
The solution is to continue using a data lake for what it does well, and augmenting it with a modern, real-time enterprise analytics environment that is designed for performance at scale.
In this paper, you’ll learn how Yellowbrick has re-thought Massively Parallel Processing (MPP) analytic database architecture across storage, CPU, networking, and software to create a specialized platform that finally delivers on the data lake promise.