The past 15 years have seen tremendous developments and enterprise adoption in the world of big data and analytics. Starting with Hadoop at early adopters like Yahoo! and Facebook, this platform provided a robust and scalable starting point for these modern big data initiatives. Although the term didn’t exist at the time, these companies were among the first to build and manage Hadoop-based data lakes.
Fast forward to 2018 and the term “data lake” has become a pervasive component of virtually every enterprise data architecture. However, the nature of the data lake has changed significantly over the past few years – and the emergence of cloud has changed the way enterprises look at data lakes.
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