Databases Reference
In-Depth Information
companies. Enterprise means across your entire company, regardless of the size.
Similar problems have been observed for organizations of any size, from single
line of business to global conglomerate.
Data architecture provides the umbrella to help an organization meet these
overarching data warehouse goals. It is time to look more closely at the
different parts of the data warehouse data architecture. Keep in mind that
the specific business and systems requirements of each organization must be
taken into consideration when developing the data architecture.
Components of DW Data Architecture
Any architecture can seem daunting to understand, but it does not need to be.
As shown in Figure 9-2, the overall flow of data in a data warehouse consists
of several basic layers, which need to be defined by the data architecture.
Capture/Create
the Data
Extract
the Data
Prepare
the Data
Publish
the Data
Use
the Data
Figure 9-2
Layers of data architecture data flow
Thefirstlayerofthedataarchitectureisforcapturingorcreatingthedata.
This is not within the realm of the data warehouse, but is done by the
source systems. The specific architecture of the source systems is determined
independently of the data warehouse, but this is where you begin. The second
layer is the process to get the data from wherever it currently lives in the
organization. This may be a simple extract from a database or a complex set
of programs to pull the necessary data, or a utility to pull the data from a
third-party application such as a financial system. The third layer is to prepare
