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In simple words, Data management is the development and execution of architectures, policies, practices and procedures in order to manage the information lifecycle needs of an enterprise in an effective manner.
Technically, 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.
Corporate Data Quality Management is the whole set of activities intended to improve corporate data quality (both reactive and preventive). Main premise of CDQM is the business relevance of high-quality corporate data. CDQM comprises with following activity areas
In modern management usage, one can easily discern a trend away from the term 'data' in composite expressions to the term information or even knowledge when talking in non-technical context.
Thus there exists not only data management, but also information management and knowledge management. This is a misleading trend as it obscures that traditional data is managed or somehow processed on second looks.
The distinction between data and derived values can be seen in the information ladder. While data can exist as such, 'information' and 'knowledge' are always in the "eye" (or rather the brain) of the beholder and can only be measured in relative units.