The concept of a ‘data lake’ was coined by James Dixon of Pentaho Corp. and this is what he said – If you think of a datamart as a store of bottled water – cleansed and packaged and structured for easy consumption – the data lake is a large body of water in a more natural state. The contents of the data lake stream in from a source to fill the lake, and various users of the lake can come to examine, dive in, or take samples. Think of a data lake as an unstructured data warehouse, a place where you pull in all of your different sources into one large “pool” of data. In contrast to a data mart, a data lake won’t “wash” the data or try to structure it or limit the use cases. Sure, you should have some use cases in mind, but the architecture of a data lake is simple: a Hadoop File System (HDFS) with lots of directories and files on it.