Certified Data Vault Data Modeler (CDVDM)
Three-day training on designing scalable, flexible and future-proof data warehouses using the internationally recognised Data Vault methodology. In partnership with Genesee Academy.
The three-day Certified Data Vault Data Modeler training teaches you how to design scalable, flexible and future-proof data warehouses using the globally recognised Data Vault methodology.
In this English-language training, developed and delivered by our partner Genesee Academy, you dive into the building blocks of Data Vault modelling and learn how to apply them within modern data architectures such as Data Mesh, Data Lakehouses and hybrid environments.
What can you expect?
You follow a powerful combination of e-learning, classroom sessions and interactive exercises. You work with realistic use cases, dive into techniques such as CBC (Consistent Business Key), NBR (Non-Breaking Record) and RDH (Raw Data History), and learn how to design robust, traceable and auditable data models. At the end of the training, you sit an internationally recognised exam.
What will you learn?
After this training:
You understand the core principles of Data Vault modelling;
You can apply CBC, NBR, RDH and other Data Vault concepts effectively;
You are able to design data models that are scalable, flexible and maintainable;
You know how to integrate Data Vault within modern environments such as Data Lakes, Mesh or cloud-based architectures;
You have all the knowledge to pass the Certified Data Vault Data Modeler exam.
Training setup
The training is delivered in English by the certified and experienced trainers of Genesee Academy. You complete a self-study programme in advance and work with hands-on assignments during the classroom sessions.
Why take part?
In the world of modern data warehouses, flexibility, scalability and reliability are essential. With Data Vault you have a proven, standardised method to keep complex data landscapes manageable.
Want to learn how to model according to the standard for modern data warehouses, backed by an internationally recognised certificate?
Sign up today and become a certified Data Vault expert!
The CDVDM training consists of three components that together create an in-depth, practical learning experience:
E-learning and self-study, around 10 hours, scheduled flexibly
3-day classroom training, on-site or live online
Online certification exam, internationally recognised
1. E-learning: solid foundation at your own pace. You start with 30 video lessons that prepare you for the classroom sessions. You learn:
The core principles of Data Vault
Architecture, scalability and business agility
Hubs, Links and Satellites, including hands-on labs
Point-in-Time and Bridge Tables, User Grouping Sets
From traditional models to Data Vault
Practical business cases and common mistakes
2. Classroom training: 3 days of interactive learning, 35% theory, 40% labs, 25% discussion
Loading and Querying in a Data Vault environment
Golden Rules and the logic behind load cycles
Delta processing, error handling and compliance
Business constructs such as SLAs, views and error codes
Strategies for management and optimisation
Bonus: 2 weeks of online follow-up after the training
3. Certification: prove your expertise
After the training you take an online proctored exam (2.5 hours, closed book).
You pick your own exam date. The exam tests your knowledge of:
Data Vault concepts and applications
Ensemble Modeling
Practical modelling and business alignment
Language: exam in English; answers may also be given in Dutch.
Result: you receive your official certificate within 4 to 6 weeks.
Resit: free, by arrangement.
After successfully completing this training and the exam, you receive the internationally recognised Certified Data Vault Data Modeller (CDVDM) certificate. This certificate is proof of your expertise in modern data modelling.
Audience
- Data and information architects
- Business analysts and data architects
- BI and DWH specialists
- Project managers and functional designers
- Data engineers
Prior knowledge
No specific prior knowledge required. Affinity with data modelling or data warehousing is an advantage.