Data Modeling — Part 1
Why should you understand Data Modeling?
We design digital products and services. This basically means that we’re designing software-based products. Now, a software has 2 main parts: data structures and algorithms. An algorithm processes input data and produces output data, and these data pieces have predefined data structures.
You might ask why you should understand this stuff. I believe that you can’t design a coherent digital product/service without defining the datatypes and their relationships. Data modeling is the activity that will help you in this regard.
There are 3 “layers”, 3 model types:
- Conceptual Model
- Logical Model
- Physical Model
In this sketch, I introduce Conceptual Models.
Example
Here is an example for you: let’s say you’re designing a job platform. What are the main part of this system? For instance — among other things — , you have job seekers, employers and available jobs. These are the objects/entities, that are usually indicated as nouns in your model. The relationship between these models are represented by verbs, for example: employers have available jobs.
After creating the Conceptual Model, the next step is assembling a Logical Model (and then a Physical Model), this is going to be the topic of the next sketch!
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Related Sketches
Recommended Reading & Useful Links
- Why data modelling is so important to user experience design
- Conceptual Models — What Are They and How Can You Use them?
- L. Yilmaz, W. K. V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti (2015). Conceptual Modeling: Definition, Purpose and Benefits
- Data Modeling 101
- We Think Therefore It Is — Conceptual Modelling for Mobile Applications
- Conceptual Modelling in an Agile World: The key to good UX!
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