Page 92 - Data Architecture

Chapter 2.1: The End-State Architecture—The “World Map”
Data marts—the place where individual departments have their customized analytic data
Applications—the operational applications where day-to-day transactions are run
ETL—the process by which application data are transformed into corporate data
ODS—operational data store—a hybrid structure where integrated data can be quickly accessed online
The archival facility—the process by which older data are removed from active analysis
The refine process—the process by which bulk data are processed and entered into active analysis
Bulk data warehouse—the data warehouse where the single version of the truth data with a low
probability of access is stored
The bulk data vault—the data vault where data with a low probability of access are stored where
rigorous data governance can be done
The data lake—the place where very large volumes of data are stored
The bulk data mart—the data mart built to manage large volumes of data
The data pond—the place where selective subsets of data are stored
Automated generation of data—the mechanism by which large volumes of data are generated
The landing zone—the place where large volumes of data are first touched by the system and are
available for processing
Data lake transformation—the process by which large volumes of data are edited and manipulated

Each of these components will be defined and discussed throughout this book. Each of
these components has their own properties. There is a distinct value to each of these
components.

Different Kinds of Data in the End State Architecture

There are many ways to understand the end-state architecture. One of the easiest ways to
understand the architecture is to examine the different kinds of data that are found in
different places.

Fig. 2.1.2 describes some of the different kinds of data found throughout the architecture.

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