Data Quality – Simple 6 Step Process

We all heard of many horrors of poor data quality. Companies with millions of records with “(000)000-0000” as customer contact numbers, “99/99/99” as date of purchase, 12 different gender values, shipping addresses with no state information etc. The cost of ‘dirty data’ to enterprise and organizations is real. For example, US Postal Service estimated that […]