Data rule analysis techniques

Business or data rules are often presented in a complex, compound manner. This is often the product of approaching rules from the standpoint of an existing technical evaluation, such as SQL. To establish effective data rule definitions, it is useful to start by looking for building blocks for the rule (such as noting that a quantity must be in a specific range).

Working from those building block conditions, you can test and debug pieces to ascertain results, then incrementally add conditions as needed, or take advantage of rule sets to combine conditions instead of building all into one rule.

This last note is of particular importance. Technical tools or languages such as SQL often require putting many compound conditions together to understand whether a record passes or fails a series of conditions. However, many of these tools do not provide the ability to break down and evaluate the individual conditions and how they relate together. The rule set support in IBM® InfoSphere® Information Analyzer allows you to look for the individual components and then assess together so that problems with any or all conditions emerge.