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Data Modeling Basics (Part 1)

Data Modeling is one of the basic skills that a Data Architect should have.

I first learned about Data Modeling in 2007 back when I was a Data Architect in Accenture Philippine Delivery Center. My first data model was for an internal application that processes all expenses incurred by employees when they go on global transfers or travel for clients.

We used the PowerDesigner data modeling tool (which is now part of SAP).

Since that time, I have been involved with several projects in career. Some required me to explicitly do data modeling; some do not. What I realized is that data is a very critical component of all enterprise and business applications. And when the data structure in these applications are not designed correctly, there is a fundamental impact to how the application will perform for the business users.

That is why, I believe that data modeling is a very important skill.

There are several definitions for Data Modeling. The one I like is the description by Steve Hoberman. According to him, "data modeling is the process of learning about the data, and the data model is the end result of the data modeling process." He also described data modeling as "feeling the data".

So, what is a data model?

Before we define what is a data model, let’s start with understanding models and why we use them.

Most people like to use models to simplify or communicate complex ideas, concepts or things.

According to the book The Change Book by Mikael Krogerus and Roman Tschappeler, “we tend to perceive things first in images, then in words. We remember pictures better than text and are more likely to recognize patterns in images than in sentences.”

Examples of models include: the double-helix model of our DNA, a schematic of how chemicals gets transported to our atmosphere and storm paths.

Here is an example of a data model.

According to Hoberman (2009), "A data model is a wayfinding tool for both business and IT professionals, which uses a set of symbols and text to precisely explain a subset of real information to improve communication within the organization and thereby lead to a more flexible and stable application environment."

In the next parts of this blog, we will talk about the three different styles of data models i.e. Conceptual Data Model (CDM), Logical Data Model (LDM) and Physical Data Model (PDM).

Disclaimer

Any external linked site(s) referenced in this blog are owned by their respective owners and are not part of this blog. In addition, the author may at times will not be able to verify fully the information in these external sites.

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