Good data quality is not only about setting proper rules, KPIs and governance. It takes a lot of effort both to establish right environment and also to transform already existing data according to established rules and policies. These are necessary activities in order to have a proper view on the progress of implemented solutions and right trends on KPIs.
Data cleansing is also a crucial activity during any data migration activities. As a result, we are able to prevent improper data from being entered into our systems. Regular house cleanings should also become a good habit for data management teams. It should be done on regular basis as a source of information regarding relevance and effectiveness of data quality rules.