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Data management comprises all the disciplines related to managing data as a valuable resource. The official definition provided by DAMA International, the professional organization for those in the data management profession, is: “Data Resource Management is the development and execution of architectures, policies, practices and procedures that properly manage the full data lifecycle needs of an enterprise. This definition is fairly broad and encompasses a number of professions which may not have direct technical contact with lower-level aspects of data management, such as relational database management.
Data management is the development, execution and supervision of plans, policies, programs and practices that control, protect, deliver and enhance the value of data and information assets. During this period, random access processing was not competitively fast, so those suggesting “Process Management” was more important than “Data Management” used batch processing time as their primary argument. As applications moved into real-time, interactive applications, it became obvious to most practitioners that both management processes were important.
If the data was not well defined, the data would be mis-used in applications. If the process wasn’t well defined, it was impossible to meet user needs. CC CDQ, University of St. Main premise of CDQM is the business relevance of high-quality corporate data.
CDQM comprises with following activity areas:. Corporate Data Quality Controlling: Effective CDQM requires compliance with standards, policies, and procedures.
Compliance is monitored according to previously defined metrics and performance indicators and reported to stakeholders. Corporate Data Quality Organization: CDQM requires clear roles and responsibilities for the use of corporate data. The CDQM organization defines tasks and privileges for decision making for CDQM. Corporate Data Quality Processes and Methods: In order to handle corporate data properly and in a standardized way across the entire organization and to ensure corporate data quality, standard procedures and guidelines must be embedded in company’s daily processes.