Building an effective data governance framework
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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.
Data life cycle management (DLM) is a policy-based approach to managing the flow of an information system's data throughout its life cycle: from creation and initial storage to the time when it becomes obsolete and is deleted. Several vendors offer DLM products but effective data management involves well-thought-out procedures and adherence to best practices as well as applications.
There are various approaches to data management. Master data management (MDM), for example, is a comprehensive method of enabling an enterprise to link all of its critical data to one file, called a master file, that provides a common point of reference.
The effective management of corporate data has grown in importance as businesses are subject to an increasing number of compliance regulations. Furthermore, the sheer volume of data that must be managed by organizations has increased so markedly that it is sometimes referred to as big data.
Big data management is the organization, administration and governance of large volumes of both structured and unstructured data. Corporations, government agencies and other organizations employ big data management strategies to help them contend with fast-growing pools of data, typically involving manyterabytes or even petabytes of information and a variety of data types.
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