There are many technologies that apply to creating and maintaining an effective data quality assurance program. Professionals in this area need to be familiar with all of the primary ones: data profiling, data cleansing, metadata repositories, data filtering, and data monitoring. This book is focused on data accuracy. The most important technology for data accuracy is data profiling. The remainder of this book is devoted to that single technology.

Data profiling is defined as the use of analytical techniques to discover the true structure, content, and quality of a collection of data. It uses as input both any known metadata about the data and the data itself. The output of data profiling is accurate metadata plus additional information on content and quality of the data.

For purposes of data quality assurance, data profiling is a process used to discover the presence of inaccurate data within a database. The more data profiling you do, the more inaccuracies you dig out. The information discovered becomes facts used to form data quality issues that need resolution.

Data profiling is a new technology that has emerged in the last few years. Practitioners have been using ad hoc methods as a substitute for formal data profiling for many years. Because they lacked a formal methodology and analytical tools designed specifically for...