The static schema-based approach may not work in following scenarios Source data keeps changing, New attributes keep getting added or removed The data needs to be viewed from different systems (Analytic cubes, Services etc ) Time to market is less The model should be adaptable to change with minimum effort The traditional modeling present the following challenges · Model needs to modify every time there is a change in the data o This involves a lot of Data architect's effort, DBA effort, and system downtime · Changes in ETL flow · Testing effort The approach is explained with a common business scenario A traditional bank has acquired a new payment gateway and needs to incorporate the user activity of the system to the existing data warehouse The user activity is stored in MongoDB and comes as a file with varying fields to...