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It is easier to agree "data quality is important" than it is to agree on the best approach to improve data quality.  Data quality issues perpetuate and often surface in business processes far removed from where they originated. It is tempting to apply a data cleansing where an issue is realized rather than where it originated for fear that changing the source may impact others.  Without clear expectations on data quality or repeatable and verifyable policies in place during system development and deployment, companies are relegated to application bugs and data fixes in production environments.  It is no wonder that organizations and projects with poor quality standards require a larger production support infrastructure and budget.

Enterprise data quality initiatives exist outside of any particular project. They provide guidance and resources to create a culture where quality metrics and processes are imbedded into every project, every system, and every process. Culture change is often difficult and can be very political in nature. Knowing where to start, how to quantify data quality, and how to change an organizational culture are keys to improving the information needed to scale your business.