Introduction to the Data Management Tier

The key purpose of the Management Tier is to acquire data from the Raw Zone of the Intake Tier and package it so that the data is ready for exploration, discovery, provisioning, and consumption by the end users or applications. The Management tier is a logical intermediary that bridges the gap between the raw data available in the Intake Tier and the discovery efforts performed in the Consumption Tier.

Tip

It is important to recollect that most of the steps in the Management Tier are potentially optional. In many practical implementations of the Data Lake, it is evidenced that the data is directly consumed from the Raw Zone of the Intake Tier. This is true in cases where the raw data is needed for data exploration and building analytical models. Hence, in such cases, all the steps that are part of the Management Tier are deemed optional.

The following figure represents the end-state architecture of the Data Lake as discussed in Chapter 1, The Need...