We will introduce you to the virtuous cycle of Data Quality (DQ).

(1)Assess – identify the current impact poor quality data is having on the organisations data. This can be achieved by a combined top-down and bottom-up assessment approach as well as DQ requirements analysis

(2)Define – defining the DQ measures, or dimensions and engaging with the data consumer to define metrics and acceptability thresholds

(3)Design – designing data standards, metadata management, business rules and designing DQ in to the system

(4)Deploy – cleansing existing data, correcting processes, identity resolution and enhancement, identifying root cause and managing remediation

(5)Monitor – inspection and monitoring. The DQ SLA and incident and performance reporting

Our consultants have a wealth of experience in all of the above phases and can relate to real world examples, knowing the pitfalls and short-cuts to avoid. We can recommend and help implement the appropriate tools to help manage all of the above.