About the Presentation

Because of the adverse impacts that poor quality data can have, organizations have begun to increase the focus on data quality in business in general and they are viewing data as critical assets like others such as people, capital, raw materials and facilities.

Since the data quality field is experiencing explosive growth, many companies have started to realize the importance of having a dedicated data quality (DQ) program to ensure that the data is fit for the intended purpose.

This presentation aims at outlining a holistic DQ approach that businesses can adopt to energize their DQ innovation processes, perfect their data gathering and usage practices and ensure robust and reliable data is available to make judicious decisions.

The proposed DQ approach that is based on DAIC (Define, Assess, Improve and Control) project life cycle, is a structured, systematic, and disciplined approach to ensure that we are getting satisfactory levels of data by minimizing cost of low quality data. This in turn, strikes a balance between rigor and creativity resulting in reduced DQ assessment and issue resolution times.

The presentation also includes some case studies from large organizations.