Monitoring Data Quality Performance Using Data Quality Metrics With David Loshin

Organizational data quality management is often introduced in reaction to acute problems traceable to how some data failure adversely affected the business. This reactive approach may be typified by a rush to identify, evaluate, and purchase technical solutions that may (or may not) address the manifestation of problems, as opposed to isolating the root causes and eliminating the source of the introduction of flawed data. In more thoughtful organizations, the business case for data quality improvement may have been developed as a result of assessing how poor data quality impacted the achievement of business objectives, and reviewing how holistic, enterprise-wide approaches to data quality management can benefit the organization as a whole, As is discussed in one previous paper.