Am often reminded in visits to the enterprise that data quality is not often enough considered carefully. You don't have much if you don't have quality. Consider also the quality and nature of meta data involved. It is even more important as you move beyond BI to heavily leveraged analytics. Bigger risks emerge. Having a process model of your data can alert you to issues about quality and change.
Data Quality in BI: It’s More Than Putting Lipstick on a Pig! Published by Pat Hennel
Data Quality and BIData quality is one of the biggest challenges that enterprises face when it comes to business intelligence. If the data isn’t accurate, inferior reporting and poor business decisions that can have potentially serious consequences on the entire organization can occur.
When first examining the quality of data as you implement a business intelligence (or BI) solution, there are a number of things that need to be considered and several questions that you need to ask yourself. For example, as Paul Dorsett shared in one of his blog posts, Self-Service BI: Fill It Up!: