Information requirements for master data management systems change over time and they must be able to accommodate a great variety of data formats. For example, in typical customer data integration efforts, there are many new ways to categorize customers and new ways of following up with customers. In product master data management efforts, there are new ways of managing product information and new types of features that arise over time. New information laws often require new processes and new types of master data.
How can we design a master data management system with a solid, stable foundation to avoid huge costs and time when information requirements change?
In this presentation, Len Silverston, best-selling author, will share his latest work on re-usable patterns from his newly released book, The Data Model Resource Book: Volume 3: Universal Patterns for Data Modeling. These patterns can be used to help establish the appropriate level of flexibility when developing data models for master data management systems, thus allowing for adaptability when information requirements are likely to change. Based upon many years of research and experiences implementing these types of patterns, he will share examples of modeling choices ranging from very specific styles of modeling to more flexible and abstract styles of data modeling for master data management solutions. In this seminar, you will learn:
- Specific examples of very common patterns, such as ways to categorize data as well as manage states, that are needed for data modeling within master data management solutions
- Various ways to model these patterns from specific styles to more generalized styles
- The pros and cons of modeling these patterns different ways
- Examples of how other master data management efforts have implemented flexible solutions and improved quality while reducing costs by using these patterns
SQL Server Research Library
