Page 109 - Data Architecture

Chapter 3.1: Transformations in the End-State Architecture

Fig. 3.1.1 The proliferation of data.

When you look at the simple example shown in Fig. 3.1.1, it is hard to argue that there is
no redundancy of data found in the end-state architecture. The example proves that—in
fact—there is redundancy of data. However, there is more to the example than meets the
eye. The redundancy of data found in the end-state architecture deserves a more careful
scrutiny.

While it is true that there is redundancy of data in the end-state data architecture, there
are some very good and very powerful reasons for the redundancy.

Transformations

In order to understand the role that redundancy of data plays, it is necessary to
understand the transformations of data found in the end-state data architecture. There are
several major transformations of data found in the end-state data architecture. Those
transformations are the following:

The transformation of text into a database format—textual ETL
The transformation of application data into corporate data—ETL
The transformation of corporate data into customized analytic data—dimensional modeling
The transformation of corporate data into bulk corporate data
The transformation of automatically generated data into a data lake
The refinement of bulk data into corporate analytic data

There is a good reason for each of these transformations.

When you look at the larger picture of what is going on, the creation and proliferation of
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