Business Intelligence projects start out as a simple report or request for an extract of data. Once the base data is aggregated then the next request usually is about summing data or creating more reports that have different views to the data sets. Before long complex logic comes into play and the metrics coming out of the system are very important to many corporate wide citizens. "Centrally managed business rules enable BI projects to draw from the business know-how of a company and to work with consistent sets of business logic they are what add the intelligence to business intelligence."(pg14) Once reports are no longer a straightforward representation of base data they begin to depend more and more on business rules. The term itself "business rule" has a variety of meanings. In our text it is defined on page 87 as "a statement that defines or constrains some aspect of the business. It is intended to assert business structure or to control or influence the behavior of the business
rules prevent, cause, or suggest things to happen" (Guide Business Rules Project,1997). Ronald G Ross provides his version in this article as "Business rules are literally the encoded knowledge of your business practices" (pg14) from the business side and "an atomic piece of reusable business logic"(pg14) from the IT side. They are so important that this needs to be understood to go farther because the rules give meaning to the numbers. They allow us to come up with insightful reports which give us a useful interpretation of raw data. Ultimately we can act on this information and save time not only for operational BI but also for root-cause analysis. For the IT side these rules are the ETL (Extract, Transform, Load) process side of a data warehouse or within BI tools themselves. "A better way to encode business logic is through an independent description of rules in a separated module." I work in the finance industry and many trading compliant systems work exactly that way...
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