While the goal of data delivery is to provide easier access and manipulation of business information, the goal of data management is to turn raw source data into useable business information. This is accomplished by integrating source data from disparate heterogeneous systems. Much of that source data is dirty in terms of data content, and much of it is misplaced or misused in old file structures. This seminar teaches you how to accomplish the data management aspect of your data warehouse project through the discipline of logical data modeling. Participants work in teams as they apply all of the learned logical data modeling rules to a case study.
Students simulate a real project by playing the roles of end user, data modeler and facilitator.
They will experience the difficult choices they will have to make when modeling ambiguous requirements, resolving data disputes between users, staying within the scope of the project and dealing with dirty data. Cross-organizational development e. Data management objectives f. Data delivery objectives 2. Entity-Relationship diagram e. Entity definitions 5. Dirty data symptoms c. Final modeling considerations 8.