December 2017
Intermediate to advanced
468 pages
13h 12m
English
The JIT transformation pattern is the best fit in situations where raw data needs to be preloaded in the data stores before the transformation and processing can happen. In this kind of business case, this pattern runs independent preprocessing batch jobs that clean, validate, corelate, and transform, and then store the transformed information into the same data store (HDFS/NoSQL); that is, it can coexist with the raw data:

The preceding diagram depicts the datastore with raw data storage along with transformed datasets. Please note that the data enricher of the multi-data source pattern is absent ...
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