What is Data Vault?
Data Vault is a robust methodology designed to create a data warehouse using a business data model. This approach focuses on integrating data from any source system and storing it in its raw form, allowing for maximum flexibility and reusability across multiple business cases. By maintaining the raw data, organizations can ensure that they have a comprehensive and accurate foundation for all future data analysis and reporting needs.
Data Vault Architecture
The architecture of Data Vault is structured into several layers, each serving a specific purpose in the data warehousing process:
- Staging Layer: Collect raw data from every source system unchanged.
- Raw Vault: Store data in original form with Hub–Link–Satellite, ensuring full lineage.
- Business Vault: Apply business rules and calculations without overwriting history.
- Information Mart: Reshape data for fast analytics and reporting.
Core entities: Hub – Link – Satellite
At the heart of every Data Vault model lie three entities that keep your warehouse agile and fully auditable.
Hubs — Unique business keys: Stores the immutable identifier of a business concept, e.g. Customer_ID or Product_Code.
Links — Relationships: Captures transactions or associations between hubs, e.g. Customer placed Order
Satellites — Descriptive & historical attributes:Keeps context (attributes, timestamps) and full history without touching the Hub or Link.
Why choose the Data Vault methodology?
Unlock governed agility, full lineage and unlimited scalability.
Bridging business and IT
The Data Vault methodology serves as a common ground between business and IT, facilitating better communication and understanding. It ensures that both parties are aligned in terms of data requirements and usage.
Agility and flexibility
Data Vault is designed to be agile, allowing for quick adaptation to changes in business requirements without the need for extensive rework. This agility supports rapid development and deployment of new features and functionalities.
Historical tracking by design
With its inherent structure, Data Vault provides historical tracking by design. This means that all changes to data are captured and stored, enabling comprehensive historical analysis and reporting.
Auditability
Data Vault ensures auditability by maintaining a complete and accurate history of data changes. This is crucial for compliance and regulatory requirements, as it allows for transparent tracking of data lineage and transformations.
Reusability of raw data
The methodology promotes the reusability of raw data for new and incoming use cases. This ensures that data is not duplicated unnecessarily, reducing storage costs and improving data integrity.
Want to see how Data Vault compares with other methodologies like Data Lakehouse or Medallion? Check out our page at beVault Data Vault Automation Tool.
They trust us
How beVault enhances your Data Vault experience
Looking for a Data Vault automation platform that balances governance, agility and cloud freedom?
beVault combines visual data modelling, end-to-end ELT pipelines and multi-cloud SQL generation in one tool.
Below are four reasons why teams choose beVault to industrialise their Data Vault 2.0 projects.
100% Data Vault compliant design
beVault follows the official Data Vault guidelines, so your warehouse is always reliable and easy to audit.
Business-friendly UI
A visual, drag-and-drop screen lets anyone sketch new data ideas and see where the information comes from. No coding needed.
Full data flow on autopilot
beVault moves the data from source to report for you—building every step and keeping them in sync.
Fits any platform
Whether you use cloud or on-prem, beVault adapts and runs smoothly without locking you to a single vendor.
Ready to revolutionize your Data Management?
Discover how beVault can transform your approach to Data Vault. Contact us today for a personalized demonstration and begin your journey towards more agile, flexible, and powerful data management.