Successful Definitions for Data Management
All data professionals acknowledge the importance of definitions, but there is very little guidance on how to create them, and what constitutes a good quality definition. While there are tools that can store and manage definitions, the content of definitions presents difficulties to many practitioners Yet without good definitions many practical problems can arise. For instance, it may be uncertain whether a source attribute really is the same as what is expected by a target. Indeed, definitions are especially necessary for source data analysis and data integration.
This webinar examines what definitions consist of and how high quality definitions can be produced. It highlights the fact that definition is as much process as product, and seeks to dispel common myths about definitions that often negatively impact the work of data professionals. These myths include the notions that definitions should be known at the start of a task, and that definitions should be highly abbreviated. The importance of separating the aspects of definitions that are business-centric from the aspects that are data-centric is explained. Particular attention is paid to the use of definitions in the area of data integration.