A discussion is provided of data governance as an information strategy that can lead to success in management of quality, consistency, usability, security, and available of company data. Knowledge workers need good data, and data quality standards are now the law under the Sarbanes-Oxley Act, for instance. To obtain high quality data, all data owned by the organization also has to be of high quality. A foundation is the first step, and commitment is the foundation for any data governance strategy, followed by technology, process, and accountability. Strategy and execution are partners, and the result will be a strategic blueprint, rather than a governance methodology. The principles highlighted can be followed with a methodology of choice. Commitment involves the ability to obtain adequate funding, and the easiest way to do so is to align data governance with the ability of the organization to be profitable. For instance, data governance could be shown to be an investment that would improve customer service, resulting in less churn and more profit from customer relationship management (CRM). Technology has to best-of-breed and able to move data through data processing systems, so the best databases, tools (including those for enterprise application integration (EAI), and extraction, transformation, and loading), data quality products, and business intelligence (BI) suites have to be purchased. A data governance group of leader has to be appointed. A good choice is a lead governance steward with a council composed of business and IT people, who is given the authority to implement, consolidate, and manage all enterprise-wide data governance activities.