Regardless of the Technology BI is about Data

Many BI projects are sold as a technology solution.  Vendors come in a wow executives with new features, visualizations, and dashboards.  Along with the software they offer simple and fast implementation that can “connect to all of your data and produce fantastic reports”.  While the technology may have the capability to connect to a variety of data sources and the software can produce reports from those connections.  They often leave out the critical question.  How clean is your data that you are reporting on?

Bad Data Ruins Great Technology

Data is the key to why you are building a business intelligence system.  Without data that you can trust and make business decisions upon, there is no reason to invest in new technology.   Before you begin a BI project, take some time to investigate the data quality of the information in the applications that will be used in any future BI Projects.  For each application you need to determine what is the appropriate level of “clean” data that can be used to make decisions.  For instance, CRM data has many components such as person, address, and contact history.  When building a BI system using CRM data the goal of the project will determine what data elements are critical for success.  If knowing how many customers you have in a location is critical then you would need to have high confidence in the address information in your CRM application.  In this instance, how clean is clean?  Having 90% of all active customer addresses with complete information?  Or is 80% of all active customers with corrected and updated address information more important?  The answer is of course, it depends.  Depending upon the expected outcome will determine what is needed from your data. Regardless of the current project, whenever you access data for a BI project your should determine what its data quality currently is.  Then make a plan to correct it short term as well as address long term needs.  Data quality that is only done once is not really data quality it is a one time clean up.  Work done on BI systems should lead the way to get your production applications to accept feedback from the BI systems as an input to fixing the source system information.