Week 6/33: Data Modelling for Data Engineering Interviews (Part #3)
What is Data Vault 2.0 and its role in Data Engineering Interviews
In this post, we explore the Data Vault modelling technique, with a focus on Data Vault 2.0. This approach has gained significant popularity recently, especially among enterprise-level organisations. As a result, questions about Data Vault are becoming increasingly common. In this post, we will cover:
What is Data Vault 2.0
Common Data Vault interview questions
Bridging the fundamental models to Data Vault
A Case Study: Converting a Dimensional Model to a Data Vault
This is the third and final post in which we will cover data modelling for data engineering interviews. If you have missed the previous posts, you can check them here: [Pipeline To Insights Interview Preparation Series]1
Note: Data Vault 2.0 is an advanced data modelling method that builds upon foundational data modelling principles. To fully grasp the concepts discussed in this post, we highly recommend ensuring a strong understanding of the following fundamentals:
ER Diagrams: Understanding entity relationships and how they map to database structures.
3rd Normal Form (3NF): The principles of normalisation and how to design databases for minimal redundancy.
Dimensional Modelling: The design of star and snowflake schemas for analytical purposes.
If you are not confident with these topics yet, we suggest starting with the post linked below to build a solid foundation:
