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
A fact qualifier matrix can identify the specific data and usage needs for data delivery. However, a successful fact qualifier matrix relies on robust data definitions Many organizations attempt to provide DW/BI/analytics users with data delivery capabilities, but the products
All data lineage initiatives should be based on a set of essential steps for effective implementation and use of the metadata Implementing a data lineage initiative is a complex, and necessary project. An established data management framework and collaboration between
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
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
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,
Data breaches are a common occurrence in organizations of every size and industry. Information Security practices and systems can help reduce the frequency and severity of data breaches.
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
Data governance professionals should take advantage of the variety of social media and social networking opportunities available to advance their knowledge, their programs, and their careers Most data governance initiatives start as a result of an event (discovery of data
