This article presents a Total Data Quality Management (TDQM) methodology for managing information quality (IQ) in organizations. The TDQM methodology is based on the principles of Total Quality Management (TQM) and aims to deliver high-quality information products (IP) to information consumers. It is designed to facilitate the implementation of an organization's data quality policy, which is formally expressed by top management. The TDQM methodology is grounded in the understanding that information should be managed as a product, similar to physical products. It involves defining, measuring, analyzing, and improving information quality continuously. The methodology is structured around a TDQM cycle, which is an adaptation of the Deming cycle used in TQM. This cycle includes defining, measuring, analyzing, and improving information quality. The TDQM methodology also includes the identification of information products and the roles involved in their production, such as information suppliers, manufacturers, consumers, and IP managers. The methodology emphasizes the importance of defining the characteristics of an IP, identifying IQ requirements, and developing an information manufacturing system that produces the IP. The TDQM methodology includes the development of IQ metrics to measure and analyze information quality. These metrics can be basic, such as data accuracy, timeliness, completeness, and consistency, or more complex, involving business rules and other factors. The methodology also includes the analysis of IQ problems to identify root causes and the improvement of IP quality through continuous improvement processes. The TDQM methodology is supported by research and practical experience, and it has been shown to be effective in improving information quality, particularly when top management has a strong commitment to data quality. Organizations of the 21st century must harness the full potential of their data to gain competitive advantage and achieve strategic goals. The TDQM methodology provides a framework for achieving this goal.This article presents a Total Data Quality Management (TDQM) methodology for managing information quality (IQ) in organizations. The TDQM methodology is based on the principles of Total Quality Management (TQM) and aims to deliver high-quality information products (IP) to information consumers. It is designed to facilitate the implementation of an organization's data quality policy, which is formally expressed by top management. The TDQM methodology is grounded in the understanding that information should be managed as a product, similar to physical products. It involves defining, measuring, analyzing, and improving information quality continuously. The methodology is structured around a TDQM cycle, which is an adaptation of the Deming cycle used in TQM. This cycle includes defining, measuring, analyzing, and improving information quality. The TDQM methodology also includes the identification of information products and the roles involved in their production, such as information suppliers, manufacturers, consumers, and IP managers. The methodology emphasizes the importance of defining the characteristics of an IP, identifying IQ requirements, and developing an information manufacturing system that produces the IP. The TDQM methodology includes the development of IQ metrics to measure and analyze information quality. These metrics can be basic, such as data accuracy, timeliness, completeness, and consistency, or more complex, involving business rules and other factors. The methodology also includes the analysis of IQ problems to identify root causes and the improvement of IP quality through continuous improvement processes. The TDQM methodology is supported by research and practical experience, and it has been shown to be effective in improving information quality, particularly when top management has a strong commitment to data quality. Organizations of the 21st century must harness the full potential of their data to gain competitive advantage and achieve strategic goals. The TDQM methodology provides a framework for achieving this goal.