If we wait until wrong decisions are made by customers relying on the bad or inaccurate data - we are in trouble. Data quality is often overlooked and yet there is no well-defined testing process or that provides guidance around ways to improve, maintain and monitor the data quality in any data-centric project. With the absence of any specialized testing tools that can aid in testing for data quality makes the entire situation even tougher. However the bad times are now over and with tools like upcoming SQL Server "Denali" Data Quality Services (DQS) we can turn the tables around. This artifact will show you how by using Denali DQS but it can be also applied on the other tools which have similar capabilities.