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Organizations need a strategy for managing metadata. This strategy should be part of an enterprise data strategy, enabling the management of data as an organizational
Following some proven guidelines for data integration will ensure success in data warehousing and business intelligence, analytics and related systems initiatives. Introduction Almost every Chief
Physical data models should follow the logical data model as closely as possible, while adding the optimizing items to conform to a specific database and
Text, the basis of language, can be considered to be unstructured by technicians. However, for others, text and language have a definite structure. It is
A managed metadata environment (MME) is the optimal approach to metadata architecture for meeting business and technical requirements Introduction Almost every corporation and government agency
Project management requires the use of a solid framework and an experienced project manager to ensure the success of any project, any size, in any
Reference and master data provide the contextual capabilities for transactional data. Managing reference and master data enables organizations to understand operational data and analyze disparately
Metrics and the measurements they create are essential to the success of every data governance program and every data stewardship effort. Organizations that implement any
Metadata management is one of the foundational components of an enterprise data management initiative. Many organizations struggle with its incorporation into their data management processes.
Standards are different from guidelines. Standards are firm and must be followed. Successful data warehouses use standards Introduction Many dog owners give their dogs what
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