Let us now understand the Data Consumption tier. We will start by taking a look at how the traditional approaches fail when dealing with Big Data discovery and consumption and how a Data Lake excels in this case. The subsequent sections will take you through Data Discovery and Data Provisioning in detail.
The need for Data Consumption has grown more complex as enterprises are sitting on the vast reserves of potentially valuable but undiscovered data. With traditional EDW systems, the approach for finding data from disparate sources has largely been manual, inefficient, and time-consuming. The existing BI tools tried to address this by adding various data integration features, but they essentially provide visibility only into a miniscule portion of the data. The questions meant to explore the data have to be defined upfront; these models fall apart in the Big Data age where it is very difficult to ascertain...