Data model layers, environments, tests and data quality explained
Data modelling is an essential part of Data engineering. I would say this is a must if you want to become a successful data practitioner. Building SQL transformation pipelines with multiple layers is a challenging task. During the process, it is important to keep things organised. In this story, I tried to summarise some techniques for convenient data structuring and describe the modelling techniques I use daily. It often helps me to design and develop a great data platform or a data warehouse which is accurate, easy to navigate and user-friendly.
Naming convention
Using a well-designed naming convention provides a very clear and unambiguous sense and meaning regarding the content of a given database object. It is always good to have naming policies for tables and columns in place. It simply demonstrates how mature your data warehouse is and helps a lot during the development.
Database entity names must be human-readable — at a minimum.
Maintaining the database or a DWH with this in mind improves user experience and simply makes it look more user-friendly.
