While past efforts often centered on periodic batch data cleansing activities, experts now say that data quality management must be an ongoing, enterprise-wide discipline to be truly effective. But how does an organization develop a strategy, calculate ROI, get funding, build a team, choose data quality remediation software tools -- and maintain a long-term, enterprise-wide program?
To learn more about how to develop and maintain an enterprise-wide data quality strategy, SearchDataManagement.com talked to internationally-recognized expert Larry English, founder of Brentwood, Tenn.-based Information Impact International and developer of the Total Information Quality Management (TIQM) methodology.
Attend this Podcast to learn:
- English's expert recommendations and best practices for how to get started with an enterprise-wide data quality initiative.
- How to calculate the return on investment (ROI), build a business case and get funding for enterprise-wide data quality management.
- Get more information about three of the essential components of an enterprise-wide data quality program.
- Learn how to structure enterprise data quality teams and find out what skill sets are necessary for success.
- Find out how to maintain enterprise data quality management programs -- and learn what common pitfalls to avoid.
Data Management Research Library
