There are various modeling techniques for hierarchies. Which of them performs best in dimensional modeling in Data Warehouses? And how to address various types of hierarchies with them? Let’s find out.
Hierarchies play a crucial role in dimensional modeling for Data Warehouses, influencing both the structure and efficiency of data analysis. Drawing from my own experiences in implementing data solutions for various companies, this article explores the best practices and techniques for handling various types of hierarchies in dimensional modeling. Through detailed examples and practical guidelines, I’ll navigate the complexities of dealing with different types of hierarchies to ensure robust and scalable data warehouse designs.
When working with hierarchies, it’s important to recognize their specificity and all related nuances. So before digging into modeling techniques, let’s see what quirks we can find in real-life hierarchy scenarios. The examples in this article are made-up, but inspired by actual cases I had in one of the projects implemented for a global pharmaceutical company. Even though they are significantly simplified, they still demonstrate interesting aspects of data modeling.
Let’s consider the following sample hierarchies: internal organization structure of a…
