Data Modeling a Necessity for Information Quality{5}

by Willen L
In this article, the author talks about how conceptual data modeling is a necessity. That it is impossible to have good data quality without first understanding what the data is supposed to represent. He goes on saying that if you don’t understand what the relationship thoroughly. He even uses the analogy that it’s kind of like when children attempt to solve a puzzle game and try to force the piece by pushing into it to complete the puzzle but in the end you don’t get the right picture from the puzzle. It’s the same way in databases, it seems to fit but not exactly and that could compromise information quality. He says that the conceptual data model is the picture on the puzzle box that provides the vision of what the information puzzle should look like at the end of the day. We can definitely develop a database without a conceptual data model but it’s likely to have errors that you have missed it is best to plan with a data model and use cardinalities to describe the relationships as well as understand / analyze all the relationship for improved information quality.

This article relates to us because we are starting to design data models and I think that it’s important for us to know why we are doing this and what impact it can have if we don’t. I have learned how important data modeling is and also the comparison between conceptual, logical, and physical data models and that in order to design a healthy database that has “good quality information”.

Stiglich, P., Necessity of Conceptual Modeling for Information Quality. infoadvisors. Retrieved January 22, 2012, from