Page 8 - DCAP606_BUSINESS_INTELLIGENCE

Unit 1: Introduction to Business Intelligence

Notes
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Caution There was no simple way (and often no way) for these systems to interact.
An infrastructure was required for data exchange, collection, and analysis that could supply a
unified view of an enterprise’s data. The data warehouse evolved to complete this need.

1.2.1 The Data Warehouse

The concept of the data warehouse (Figure 1.1) is a lone scheme that is the repository of all of the
organization’s data (or simply data) in a pattern that can be competently analysed so that
significant accounts can be arranged for administration and other information workers.

Figure 1.1: Data Warehouse Concept

Point of Sale
Gift Registry

Ad Hoc
Inventory Queries
ETL Batch Data Warehouse Reports
transfers

dashboards
Sales Promotions

Source: http://www.gravic.com/shadowbase/images/uses/datawarehouse.png
However, meeting this goal requires some challenges:
Data should be acquired from a variety of incompatible systems.
The identical piece of data might reside in the databases of distinct systems in distinct
types. A specific data item might not only be represented in distinct formats, but the
values of this Data piece might be distinct in distinct databases. Which value is the correct
one?
Data is continually altering. How often should the Data warehouse be revised to
contemplate a sensibly current view?

The amount of Data is massive. How is it analysed and presented easily so that it is useful?
To meet these needs, a broad range of powerful tools were developed over the years and became
productized. They included:

Extract, Transform, and Load (ETL) utilities for the moving of data from the diverse data
sources to the common data warehouse.

Data-mining pushes for complex predetermined analysis and ad hoc queries of the Data
retained in the Data warehouse.
Reporting tools to provide management employees with the outcomes of the analysis in
very simple to absorb formats.

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