The original data lake’s architecture has two severe drawbacks. One relates to the physical nature of the data lake which may kill the big data project entirely because it can be “too big” to copy to a central environment. The other relates to the restricted usage of the data lake investment – it’s designed exclusively for data scientists.
Download this whitepaper and learn how data virtualization facilitates a multi-purpose data lake by allowing a broader and greater use of the data lake investment without minimizing the potential value for data science or for making it a less flexible environment. Multi-purpose data lakes are data delivery environments architected to support a broad range of users, from traditional self-service BI users to sophisticated data scientists.