Three steps to restoring data quality:

1. Make good data definitions

Good definitions become the standards for determining data quality.
For each data element there must be a specification of its meaning, valid value range and any format requirements. And the relationships and dependencies between data elements must be clear.

2. Cleanse the existing data

Compare the existing data to the standard. Identify elements that do not conform. Determine what corrections need to be applied to the data. Apply updates to the operational data.

3. Make sure data stays clean

Data will only stay clean if the day to day change and update procedures also apply the standards.
Responsibility for data must be assigned within the organisation. The data update procedures must be understood and business rules for the data ….

How I Can Help

To carry out these steps effectively needs management commitment, involvement of those responsible for business processes and coordination by means of a project. I can bring expertise and a short term resource to do work in each project phase.