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Interactive learning

Data Vault Foundations

Lorenzo Colombani

A 14-chapter interactive learning platform — Data Vault architecture, SQL, dbt, EU compliance, Python — with quests, feedback and hands-on exercises. Independent work; for certification and enterprise Data Vault, see Scalefree.

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About this toolCase study

Behind the experience

Learn the architecture by working with it.

Fourteen chapters connect Data Vault modelling with SQL, dbt, Python and regulatory questions. The learning path is aimed at people who need to understand a warehouse by doing the work, rather than only reading about it.

Exercises give feedback as the learner progresses through the chapters. Compliance is part of the model: the course asks where sensitive attributes belong and what deletion must leave behind.

By
Lorenzo Colombani
Format
Interactive learning
Role
Learning design, interface and development
Scope
14 chapters; more than 100 exercises
Access
Free, independent learning platform
Preview
animated project screenshot

Case study

Data Vault Foundations

Who it is for

People who have to work with a Data Vault and have never built one: analysts, engineers moving to a new warehouse, and the compliance people who must sign off on it. The goal is usable understanding, not a certificate. By the last chapter you have written the SQL and taken the compliance self-test.

The curriculum

Fourteen chapters, in the order you take them. Five are regulatory.

  • Chapter 1: Ontology
  • Chapter 2: Data Vault Deep Cuts
  • Chapter 3: SQL SELECT
  • Chapter 4: SQL JOINs
  • Chapter 5: Compliance and GDPR
  • Chapter 6: dbt Tools
  • Chapter 7: EU Regulations
  • Chapter 8: Compliance Mechanisms
  • Chapter 9: AI Act and Data Vault
  • Chapter 10: SQL CREATE TABLE
  • Chapter 11: SQL Practice and dbt
  • Chapter 12: Integration Day
  • Chapter 13: Compliance Self-Test
  • Chapter 14: Python Vault Runner

Exercises and feedback

More than a hundred exercises, each answered on the spot, and quests that string them into something you finish rather than a list you abandon. The progression unlocks as you go.

The regulatory track

Five of the fourteen chapters are regulatory: GDPR, EU regulations, compliance mechanisms, the AI Act, and a compliance self-test. They treat compliance as part of the data model — which satellite holds the sensitive attributes, what a deletion has to leave behind — rather than a chapter bolted on at the end. The same question, taken further, became a paper: Engineering AI Act data governance for data teams.

Gamification

The progression logic follows Yu-kai Chou's Octalysis framework; the same reading produced the Gamification Helper Tool on this site.

Design and build

Fourteen static pages that open from one chapter portal. It runs anywhere a browser runs.

I design the product and make the technical calls — architecture, stack, interactions — then direct AI coding tools that build to my spec. I review and test everything that ships.

Where it stands

Live and free. This is independent work and this site sells no Data Vault consulting. For certification and enterprise Data Vault, see Scalefree.

From the original published project case study.

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