My first Publication Agile-Data-Warehouse-Design-eBook | Page 116

abbreviations
4
M ODELING B USINESS P ROCESSES
The only reason for time is so that everything doesn't happen at once
— Albert Einstein
Designing a data warehouse or data mart for business process measurement
demands that you quickly move beyond modeling single business events. All but
the simplest business processes are made up of multiple business events and BI
stakeholders invariably want to do cross-process analysis. When you modelstorm
these multi-event requirements you soon notice two crucial things:
BI Stakeholders
need multiple
events for process
measurement
Stakeholders model events chronologically. As you complete one event,
stakeholders naturally think of related events that immediately follow or pre-
cede it. These event sequences represent business processes and value chains
that need to be measured end-to-end. Events sequences
Stakeholders describe different events using many of the same 7Ws. When
you define an event in terms of its 7Ws, stakeholders start thinking of other
events with the same details, especially events that share its subject or object.
These shared details, known to dimensional modelers as conformed dimen-
sions, are the basis for cross-process analysis. Events share
In this chapter we describe how an event matrix, the single most powerful BEAM ✲
artifact, is used to storyboard the data warehouse: rapidly model multiple events,
identify significant business processes and conformed dimensions, and prioritize
their development.
The importance of conformed dimensions for agile DW design
Modelstorming event sequences with an event matrix
represent business
processes and
value chains
common
dimensions that
support cross-
process analysis
The event matrix is
an agile tool for
modeling multiple
events
Chapter 4 Topics
At a Glance
Prioritizing event and dimension development using Scrum
Modeling event stories with conformed dimensions and examples
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