Data quality has matured. In its early days the focus of efforts to improve the quality of data in organizations was predominantly tactical. Usually a specific data quality (DQ) problem was identified and a project initiated and delivered to resolve or ameliorate it. Examples include improving a customer marketing list, clearing redundant records of former customers, matching logical and physical inventory and so on. This approach was characterised by a heavy emphasis on data cleanse, a one off process where shortcomings were recognized, quantified and improvements made.
This paper is aimed at all involved in DQ improvement, whether primarily in business or IT roles, who are considering, initiating or actively involved in an organization wide approach to DQ improvement. It draws on the author’s experience in initiating and leading an enterprise wide DQ Program in a major global organization, British Telecommunications plc. (BT) and on consultancy engagements with global organizations and UK government departments.
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