The Data Modeling Addict - April 2010
Three Situations That Weaken Data Model Precision
Published: April 1, 2010
Steve Hoberman describes three situations that can degrade the precision of a data model.
The following is an excerpt from Data Modeling Made Simple, 2nd Edition , by Steve Hoberman, ISBN 9780977140060.
Precision with respect to data modeling means that there is a clear, unambiguous way of reading every symbol and term on the model. You might argue with others about whether the rule is accurate, but that is a different argument. In other words, it is not possible for you to view a symbol on a model and say, “I see A here” and for someone else to view the same symbol and respond, “I see B here.”
Going back to the business card example, let’s assume we define a “contact” to be the person or company that is listed on a business card. Someone states that a contact can have many phone numbers. This statement is imprecise, as we do not know whether a contact can exist without a phone number, must have at least one phone number, or must have many phone numbers. Similarly, we do not know whether a phone number can exist without a contact, must belong to only one contact, or can belong to many contacts. The data model introduces precision, such as converting this vague statement into these assertions:
There are three situations however, that can degrade the precision of a data model:
Recent articles by Steve Hoberman
Steve Hoberman -
Steve Hoberman is a world-recognized innovator and thought-leader in the field of data modeling. He has worked as a business intelligence and data management practitioner and trainer since 1990. Steve is known for his entertaining, interactive teaching and lecture style (watch out for flying candy!) and is a popular, frequent presenter at industry conferences, both nationally and internationally. Steve is a columnist and frequent contributor to industry publications, as well as the author of Data Modeler’s Workbench and Data Modeling Made Simple. He is the founder of the Design Challenges group and inventor of the Data Model Scorecard™. Please visit his website www.stevehoberman.com to learn more about his training and consulting services, and to sign up for his Design Challenges! He can be reached at firstname.lastname@example.org.