b.Schema-on-write vs. Schema-on-read: A data warehouse implements schema-on-write,
which means that data needs to be transformed into a structured form or a schema
(explained in Chapter 1) before it is stored in the data warehouse. Data storage for a tra-
ditional data warehouse is hugely expensive. As such, data warehouses, by principle, do
not store data on anticipated or speculative use at a later point in time. On the other hand,
a data lake stores all kinds of data in their raw, native formats, irrespective of structure,
thereby reducing efforts for structuring the data before it is stored. The data is formatted ...
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