How To Get Started With Data Vault 2.0
- Rhys Hanscombe
- Aug 26
- 3 min read
Updated: Aug 27
This blog post is based on episode 1 of The Business Thinking Podcast with our CEO, Neil Strange, and AutomateDV Product Manager, Alex Higgs.
Starting with Data Vault can feel overwhelming, but it doesn’t have to be. In an episode of The Business Thinking Podcast, Neil Strange and Alex Higgs shared insights on how to get started with Data Vault, common challenges, and the best ways to overcome them.
Listen to the full episode below:
Why Data Vault?
Data engineers are constantly looking for scalable, flexible data modeling approaches that support complex data integration and long-term business growth.
Data Vault is designed to handle these challenges by enabling:
Rapid iteration – Build and adapt data models quickly.
Single source of truth – Integrate multiple data sources into a unified model.
AI and machine learning support – Provide a semantic layer for AI applications.
Improved audit and data quality – Track changes and maintain data integrity.
But getting started with Data Vault can be challenging without the right guidance.
Common Challenges When Starting with Data Vault
Alex highlighted the most common issues data engineers face when starting with Data Vault:
Organizational Buy-In – Getting leadership and stakeholders to support Data Vault can be difficult.
Upskilling – Learning the concepts and technical details takes time and resources.
Lack of Hands-On Experience – Understanding the theory is one thing, but implementing it is another.
Step-by-Step Guide to Data Vault
Here’s a practical roadmap to help you get started:
1. Learn the Basics
Start by reading the official Data Vault book by the inventor, Dan Linstedt - Building a Scalable Data Warehouse. This gives you a solid theoretical foundation in Data Vault 2.0. However, theory alone isn’t enough. As with anything, hands-on experience is the best way to learn.
2. Use AutomateDV for Hands-On Learning
AutomateDV is a free package for dbt that automates Data Vault modeling. The tool works with dbt Core or dbt Cloud and generates all the SQL behind the scenes so you can see exactly how it works.
We created the tool in 2019, and it has helped thousands of data engineers simplify their Data Vault implementation.
AutomateDV supports platforms like:
Get started with AutomateDV by following our setup guide.
3. Try a Sample Project
AutomateDV provides a free sample project on GitHub with pre-configured and all necessary dbt files. The sample project includes a step-by-step walkthrough to explain the process and helps you see how a Data Vault project is structured in real-world scenarios.
Why Hands-On Experience With Data Vault Matters
As Alex mentioned in the episode:
"Just downloading something and getting stuck into it is really valuable."
Hands-on experience helps you:
Understand Data Vault’s core principles.
Solve real-world data modeling problems.
Gain the confidence to apply Data Vault in your environment.
What’s Next?
Once you’ve completed a sample project and explored the documentation, you’ll be in a strong position to:
Determine if Data Vault is the right solution for your business.
Build a case for securing funding for formal training.
Explore advanced Data Vault techniques and integrations.
At Business Thinking, we offer free Data Vault training for professionals like you who want to grasp the Core Concepts of the method.
Book your place at an upcoming live session here.