The basic structure of the cube is similar
or identical to the DSV, but then the cube can be greatly expanded. Dimensions
can have hierarchies added to them. Cubes can contain calculations that would
be difficult or impossible to do using relational tables. Cubes may have key
performance indicators, actions, perspectives, and other features available only to
cubes; features that are simply not available in relational databases.
Finally, a cube must be processed in order to read the data from the source system
or systems and store it in a structure built for the speed of retrieval. Aggregations are
often calculated at this time. Many organizations perform nightly or weekly updates,
although monthly updates are not uncommon, nor is it uncommon to perform
incremental updates throughout the day if the need for timely data is high.
Finally, once the cube is built, consumers are ready to begin accessing the data
and reaping the benefits of the BI project. The rest of this book is dedicated to the
tools that allow end users to access the data and make sense of it. The next chapter
will introduce scorecards and key performance indicators, techniques often used by
higher level management, but accessible to anyone.
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CHAPTER 4
Scorecards and Key
Performance Indicators
IN THIS CHAPTER
Key Performance Indicators
Scorecards and Dashboards
Summary
62 B u s i n e s s I n t e l l i g e n c e w i t h M i c r o s o f t O f f i c e P e r f o r m a n c e P o i n t S e r v e r 2 0 0 7
As I discussed in the first chapter, there are many different categories of
business users.
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