Data Quality is currently a relevant issue, considering that organizations sustain their operations and decision making in the data they have at their disposal. On the other hand, literature is unanimous in pointing out that poor data quality can result in large costs for organizations. The literature review identified twenty-four Critical Success Factors that were put to the consideration of a panel of experts, who ordered them according to their degree of importance, using the Delphi method with the Q-sort technique, based on an on-line questionnaire. The study showed that the five most important Critical Success Factors for Data Quality Management are: definition of appropriate policies and standards, control of inputs, definition of a strategic plan, organizational culture focused on quality of the data and obtaining commitment and support from the top management.