Data Vault Ensemble Modeling

Introduction to Data Vault Modeling

Peer M. Carlson, Dörffler & Partner

Data Vault is a comprehensive modeling system for the core warehouse focused on long-term historical storage, easy audibility/traceability, and a high resilience to change.  Business Intelligence projects that use Data Vault benefit from a variety of advantages:

  • Due to a defined set of table stereotypes – hubs, links, and satellites – Data Vault structures and loading processes can be generated automatically, using specialized tools.
  • The flexibility of the Data Vault design allows the development team to concentrate on just the set of attributes currently needed by the business, keeping the effort small.
  • Extending an existing Data Vault model at a later time comes at a very low cost.
  • When integrating business keys, the usage of hash keys enables a very high data loading speed.
  • The modeling paradigm of Data Vault fully supports agile development (e.g. Scrum) through the entire delivery pipeline.
  • … and many more.

This presentation will give a general introduction to Data Vault modeling – appropriate for those without any background in this area.  We will talk about the modeling concepts of Data Vault, particularly hubs, links, and satellites, and how Data Vault modeling affects the overall architecture of the data warehouse.  Furthermore, we will also look at Data Vault in agile development environments.

For best understanding, a general knowledge of Business Intelligence and Data Warehouse systems is required.

Peer M. Carlson is a certified Business Intelligence Consultant at Dörffler & Partner GmbH, Germany.  He consults companies in various industries on topics such as Data Vault, data modeling and dimensional modeling, as well as agile development methodologies.  As a strong supporter of conceptual modeling and design, he helps technical and business people get a better understanding of overall project requirements.  With his in-depth knowledge of database systems and DW/BI architectures, he brings individual features from the conceptual level to a practical, value-adding solution.  Peer has worked on several Scrum-driven data warehouse projects, mainly with Teradata and Microsoft SQL Server.  He holds a university degree in Computer Science with focus on Business Information System.