
Introduction and Agenda
Why Data Vault
Data Platform
Data Vault Reference Architecture
Agile Data Vault Methodology
Introduction to Data Vault Modeling
Data Vault Implementation
Data Vault Automation
Additional Resources
Why You Should Use Data Vault
Unlock Your Data’s Potential: The Data Vault Advantage
Agility, Trust, And Scale For The Modern Business
Four Pillars Of The Data Solution
Defining The Data Platform
Sourcing All Data
DIKW Pyramid
Two Phases Of Data Platforms
Data Vault Reference Architecture
Architectural Compatibility
Scalable Data Platform Of A Kitchenware Retailer
IFRS Compliant Data Vault Architecture For Insurance
Cloud Architecture For Financial Service Corporation
Managed Self-Service Architecture
Data Vault Reference Architecture
Defining The Landing Zone / Staging Area
Defining The Edw Layer
Single Version Of Truth
Single Point Of Facts
Vault Types
Multiple Raw Data Vaults Vaults
Multiple Business Vaults
Defining The Information Delivery Layer
Types Of Marts
Information Marts
One Information Mart vs Many Information Marts
Error Marts
Metrics Marts
Raw Marts
Quality Marts
Interface Marts
Source Marts
AI / Feature Marts
User Marts
Foundations
Sprint Organization
Sprint Plans
Interaction Between Teams
Call Of Duty
Scrum Of Scrum
Continuous Improvement
How To Improve Maturity?
Standards Library
Team Composition
Interaction Between Teams
Call Of Duty
Scrum Of Scrum
Information Requirements
Example
Data Vault Reference Architecture
Raw Marts
Agile Requirements Gathering
Modeling Styles
Logical Data Vault Modeling
Source Vault
Source Data
The Importance Of Business Keys
Business Key Requirements
Business Key Preference
How To Find Business Keys
What Data Is Made Of
Concept Analysis Meeting
Business Model
Phase 1: Business Objects And Relationships
Identification Of Business Objects
Identification Of Business Objects
Phase 2: Identification Of Business Objects
Is The Email Address A Good Business Key?
Business Objects / Relationships / Business Key Candidates
Focus On Concepts
Questions To Ask
Select The Best Business Key
Fundamental Components Of Data
Hub Definition
Relational Hub Structure
Link Definition
Logical Model
Relational Link Structure
Satellite Definition
Logical Model
Relational Satellite Structure
Loading The Data Lake (Psa)
Organizing The Data Lake
Relational Staging Areas vs Relational Access Layers
Loading The Raw Data Vault
Implementing The Business Vault
Creating The Information Marts
Designing Information Delivery
Before You Automate (At Scale)
Data Vault Metadata
Other Metadata
Example Automation
Available Off-The-Shelf Automation Tools
Diy Data Vault Automation
Ai-Driven Automation
Books
Articles
Scalefree Blog
Data Vault Newsletter
Case Studies
Data Vault Training
Data Vault Implementation
Datavault4dbt
Turbovault4dbt
Datavault4coalesce
Unlock your organization's data potential with "Data Vault: An Introduction by Michael Olschimke", an intensive five-hour class led by the industry authority Michael Olschimke.
In today’s fast-paced business landscape, traditional data warehousing often fails to keep up, acting like a rigid legacy software system where changing a single line of code requires a complete system reboot. This course introduces you to the Data Vault standard, a modern solution designed like a modular microservices architecture that allows you to add new data sources and business units in days, rather than months, without disrupting your existing operations. This framework is specifically built for agility, unshakeable trust, and massive scalability to ensure your data grows with your business, not against it.
The Business Value of Data Vault
Extreme Agility: Add new data sources in days with "plug-and-play" integration that avoids system reboots.
Total Auditability: Build unshakeable trust with 100% traceability for effortless regulatory compliance.
Massive Scalability: Eliminate bottlenecks with a modular design that supports parallel team development.
Rapid ROI: Slash manual coding by up to 80% through standardized patterns and automation.
What You Will Learn
This training is structured around the four pillars of a successful data solution: Architecture, Methodology, Modeling, and Implementation. You will begin by defining the modern data platform, understanding how to source all types of data—structured, semi-structured, and unstructured—regardless of the environment.
Michael will guide you through the Data Vault Reference Architecture, covering the essential layers from the Landing Zone and Staging Area to the Raw Data Vault, Business Vault, and final Information Marts. You will gain a deep understanding of core modeling components, including Hubs, Links and Satellites.
Agile Methodology and Implementation
Beyond technical modeling, this course teaches you the Agile Data Vault Methodology. You will learn how to organize sprints—from the initial "fail fast" setup in Sprint 0 to delivering production-ready business value in subsequent cycles. Finally, the training covers the critical role of Automation, introducing you to industry-leading tools like dbt, Wherescape, and Datavault Builder to streamline your data flows.
Whether you are a data architect, analyst, or IT manager, this course provides the foundational knowledge needed to build a resilient data warehouse that grows with your business, not against it.