The Most “Universal” Data Model Patterns
Len Silverston, Universal Data Models
There are some data model constructs that are so universal that they appear in almost every data model. This seminar will share many alternatives for modeling these prevalent constructs and point out the pros and cons of modeling them in various ways.
For example, modeling contact information, including traditional contact methods such as phone, fax, email, and international addresses as well as newer ways to contact someone such as Twitter, Facebook, and Skype are very common data requirements which are often much more complex than one may think. There is a common data requirement to classify data, for example, to model customer types, product categories, and many other classifications. These classifications are often modeled differently depending on the entity being modeled. By using the classification pattern and alternatives that this seminar will share, we can understand valid ways of modeling classifications and keeping our data model consistent while using high quality constructs to model classifications. Other very common data requirements are the need to model statuses, hierarchies, demographics, and product/service information.
Based upon decades of research on ‘universal’ models, this seminar will provide in-depth patterns and alternatives for modeling these constructs that are bound to be needed and that are widely useful. Participants will leave with a toolkit of the latest versions of these patterns that they can use on subsequent modeling efforts.
Participants of this session will gain:
- Effective data model templates for modeling the most common patterns in data models, such as contact information, demographics, classifications, statuses, hierarchies, roles, and product/service information
- Valid variations and alternatives in modeling these types of data models constructs and the pros and cons of these alternatives
- Exercises in using these patterns and in how to select the best choice for your modeling effort and/or organization
- Pitfalls in avoiding ineffective ways to model these critical constructs
- Options about how to model these constructs using different styles such as modeling them using a very specific style or very generalized styles and the pros and cons of these styles.
Len Silverston is a best-selling author, consultant, and a fun and top rated speaker in the field of data modeling, data governance, as well as human behavior in the data management industry, where he has pioneered new approaches to effectively tackle enterprise data management. He has helped many of the largest organizations world-wide as well as small organizations, to integrate their data, systems and even their people. He is well known for his work on “Universal Data Models”, that are described in his The Data Model Resource Book series (Volumes 1, 2, and 3), (Volume 1 was rated #12 on the Computer Literacy Best Seller List) and these books have been translated into multiple languages. He is the winner of the DAMA (Data Administration Management Association) International Professional Achievement Award for 2004 and the DAMA International Community Award for 2006. He has received the highest speaker ratings at many international conferences and is dedicated to being of the greatest service to his audiences.