Data lakes have helped organizations deal with the massive amounts of data generated daily. They are intended to serve as a central repository for raw data, a treasure trove for data scientists to analyze and gain actionable insight. They also serve as the foundation for many "self-service" analytics initiatives. While getting data into a lake is simple, getting insight and value from all of that data, however, has proven to be challenging for many organizations. A recent Forrester report found that 60%-73% of all enterprise data goes unused for analytics. This statistic exposes some of the harsh realities of data lakes. Read article…