Information Architecture
For many applications, information architecture and data modelling is limited to providing the
application logic a means of robust persistence. Thus the design of the information architecture
is driven purely by application logic and programming concerns. However for effective business
management systems of the class we are concerned with, we must assume that the data is valuable in
its own right and carries uses beyond the simple transaction processing logic of the system.
Data is a first class concern for our overall approach to business management system design. We
predicate this elevation of importance on the following assumptions:
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The business management system database will be the system of record for the majority of
material business records. This may be on a company, divisional, or departmental basis.
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Third party applications will need to consume data and may produce data which properly is
recorded in the system of record database. There may be many such applications.
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We expect that the third party reporting and business intelligence tools will be used to
provide specialized presentations and insights into the data.
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The business management system we build may be subordinate to more fundamental business
management system which acts as the system of record. This will likely be true if our
application is only supporting a division or department of a larger organization.
In all of these cases we’re describing scenarios where our business management system is planned
to be part of a larger ecosystem of collaborating applications. This is called the
“best-of-breed” approach to business systems architecture and is common feature of enterprise
applications deployments.
Business Management Systems often contain a large number of relations, often into the hundreds of
database tables, with some systems exceeding one thousand relations. And while the number of
relations required to support the broad functional concerns of the typical business management
system can be large, this data can be generalized into a relatively small handful of categories of
data.
The modelling of business relationships has evolved over time, moving from rather simple and naive
ideas to more correct representations of real world business relationships. Here we examine this
history and establish