Data warehouse contains historical data to assist in organizational decision-making. Requirements one of the most important data models that influences the accuracy of the information kept in the data warehouse and used to make critical organizational decisions. Consequently, evaluating the data warehouse's information quality becomes crucial. There aren't many studies in the literature that guarantee the accuracy of the data model—requirements for a data warehouse. However, very less work was witnessed in the literature to validate requirements completeness (decomposition and specification to be completed) metrics for evaluating the requirements model quality. Hence, in this paper Zuse’s formal framework was used to theoretically validate the requirements decompostion metrics (based on agent goal decision information model) and the results demonstrate that every requirement decomposition completeness metric is legitimate and accurately formulated. In order to ensure the accuracy of the requirements model for the data warehouse, requirements decomposition completeness metrics can be utilized.