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Information Quality Means More than Accuracy

Accuracy is not the only measurement that can or should determine quality for an organization’s data.  Data can be accurate in one context and inaccurate in another, and both versions can have value. Many people think accuracy is the sole

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Avoiding Data Mess with Effective Data Architecture

Rather than apply new words or phrases to poor data architecture concepts, learn how a data strategy should influence effective data architecture, especially for analytics and business intelligence People love buzzwords. Sometimes people think the quality of a solution improves

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EIM Framework Components and Dependencies

Every enterprise data / information management program contains aspects of several component areas, and each program should leverage the alignments and dependencies between these components for their maximum benefits and value to the organization. Many organizations find that using an

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Benefits of Documenting Data

Every data documentation effort should identify the expected benefits, often based on the context and content While defining an approach to documenting data and the relevant attributes to be documented, it is important to focus on depending on the context

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Data Governance as Part of Enterprise Data Management

Data governance is the cornerstone domain of the enterprise data management discipline.  The functions of data governance are essential to any successful enterprise data management initiative Many organizations are pursuing numerous data-oriented initiatives, such as customer integration, master data management,

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A New Approach to Agile Project Management

Data warehousing / business intelligence / analytics programs require a different approach to project management.  Quick deliverables, simplified scope, and attention to rapid results are combined in a method called “Extreme Scoping” Every organization needs a methodology to manage projects

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