1.10 Closing Remarks

1.10 Closing Remarks

As information systems become more of the fabric of organizations, they also get more and more complex. The quality of data within them has not improved over the years as has other technologies. The result is that most information systems produce data that is of such poor quality that organizations incur significant losses in operations and decision making. It also severely slows down and sometimes cripples attempts to introduce new business models into the organization.

There are many reasons data quality is low and getting lower. This will not change until corporations adopt stringent data quality assurance initiatives. With proper attention, great returns can be realized through improvements in the quality of data.

The primary value to the corporation for getting their information systems into a state of high data quality and maintaining them there is that it gives them the ability to quickly and efficiently respond to new business model changes. This alone will justify data quality assurance initiatives many times over.

Data quality assurance initiatives are becoming more popular as organizations are realizing the impact that improving quality can have on the bottom line. The body of qualified experts, educational information, methodologies, and software tools supporting these initiatives is increasing daily. Corporations are searching for the right mix of tools, organization, and methodologies that will give them the best advantage in such programs.

Data accuracy is the foundation of data quality. You must get the values right first. The remainder of this book focuses on data accuracy: what it means, what is possible, methods for improving the accuracy of data, and the return you can expect for instituting data accuracy assurance programs.