数据字典在需求分析上的作用

A data dictionary is a collection of detailed information about the data entities used in an application. Collecting the information about composition, data types, allowed values, and the like into a shared resource identifies the data validation criteria, helps developers write programs correctly, and minimizes integration problems. The data dictionary complements the project glossary, which defines application domain or business terms, abbreviations, and acronyms. We recommend keeping the data dictionary and the glossary separate.

During requirements analysis, the information in the data dictionary represents data elements and structures of the application domain (Beatty and Chen 2012). This information feeds into design in the form of database schemas, tables, and attributes, which ultimately lead to variable names in programs. The time you invest in creating a data dictionary will be more than repaid by avoiding the mistakes that can result when project participants have different understandings of the data. If you keep the data dictionary current, it will remain a valuable tool throughout the system’s operational life and beyond. If you don’t, it might falsely suggest out-of-date information, and team members will no longer trust it. Maintaining a data dictionary is a serious investment in quality. Data definitions often are reusable across applications, particularly within a product line. Using consistent data definitions across the enterprise reduces integration and interface errors. When possible, refer to existing standard data definitions from a repository of enterprise knowledge, using a smaller, project-specific set to close the gaps.