Data modelling is not only for data architects and software engineers. Anyone who works with data, including data analysts, business analysts, and business intelligence designers, needs to understand and be able to create at least simple data models.
Even simplistic entity relationship diagrams (ERDs) can help support analysis and data discovery, identify crucial relationships and clarify important groups of data.
Sometimes, a conceptual model is sufficient, and on other occasions, a starter logical model with a few attributes will work best to support business & data analysis activities. To learn more:
How To Create a Conceptual Data Model (article)
How to create a conceptual data model (video)
As I taught cohort after cohort of students in a business analytics program, I saw them struggle with the same questions, and make the same mistakes over and over when creating their first ERDs.
Here are some typical ERD mistakes. Watch this video or go to the full article to learn how to avoid them.
1. Cryptic entity names.
2. Plural entity names.
3. Too many words in entity names
4. Confusing entities and categories
5. Confusing entities and states
6. Missing identifying attributes
7. Missing time attributes
8. Confusing attributes with values
9. One-directional relationship
10. Incorrect placement of attributes linking parent and child
11. Missing one-to-many relationships
12. Confusing metrics and attributes
13. Mixing up modelling notations
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