Here's a good read from Enterprise Systems Journal-- a reminder of why data quality is important to all of our efforts, and why OWB has extensive data profiling and data quality features built in.
Of course, if you're reading this blog, you're already mindful of these issues, and are using OWB data profiling and data cleansing with all your data and auditing quality regularly... right? :)
Analysis: Data Quality is Job Number 1
BI tools are only as good as the quality of the data they work with. Analyst Michael Schiff is still surprised at how many BI professionals still ignore this fact.
By Mike Schiff
Much attention has been focused recently on integrating data from multiple sources to populate data warehouses or data marts for analysis purposes or as part of a migration effort for new enterprise applications. For example, a recent press release from a well-established business intelligence vendor highlights the ability of its BI platform to access multiple data sources where they reside without first having to move the data into a data warehouse or a data mart.
Rather than dwelling on the tradeoffs (perhaps a topic for future analysis) among centralized data warehouses, federated databases, enterprise information integration (EII), or even the old concept of virtual data warehouses, I would like to point out a common property they share: the quality of the information obtained from any of them is directly dependent on the quality of the data they access or contain. In other words, GIGO (garbage in, garbage out) always has applied (and always will apply) to both analytical and operational systems.
We all recognize this, yet I continue to be amazed as to how often we ignore the fact. In most cases, it's not deliberate; rather it results from taking at face value preliminary assumptions about data quality rather than using techniques such as data profiling to validate the assumptions.