Advanced Data Vault Tips and Tricks

Roelant Vos, Allianz Worldwide Partners

Data Vault patterns. They seem almost deceptively easy when you first look at them, but there is more to them than first meets the eye. This session intends to look beyond the initial Hub, Link and Satellite approaches and will explain what other considerations there are to be aware of, to help define a truly resilient and flexible Data Warehouse solution.The Data Vault methodology provides some elegant handles to develop your Data Warehouse – the various required Data Warehouse mechanics are organised in a way that allows for a flexible solution. But you’re still delivering an Enterprise Data Warehouse and the associated complexities will need to be addressed somewhere.When all these necessary considerations have been incorporated, the patterns start to look a fair bit more complicated. The reasoning for this, and the modelling and implementation choices you have to make along the way – as well as their consequences – will be discussed in this hour of advanced Data Vault tips & tricks.


  • Data Vault is about supporting the business in defining its requirements over time. But is it realistic to get the data model itself right in one attempt? How enhanced templates help you refactor.
  • Things you should know about the Hub, Link and Satellite patterns beyond the basics and their position in the overall design.
  • Loading multiple changes in on go using record condensing and change merging for Satellites. When is a change a change?
  • Getting data out again – ‘time flattening’ in PIT and Dimension tables.
  • The role of the ETL control framework and Referential Integrity.
  • Lessons learned – my top 5 favourite mistakes over more than a decade of Data Vault implementations.
Roelant Vos has been active in Data Warehousing and Business Intelligence for more almost 20 years and is working for Allianz Worldwide Partners as the General Manager for Business & Customer Insights in Brisbane, Australia. In a role that is highly focused on analytics, Roelant is working on collecting, integrating, improving and interpreting data to support various business improvement initiatives. Passionate about improving quality and speed of delivery through model-driven design and development automation, he has been at the forefront of contemporary modeling and development techniques for many years. Whenever there is some time updates on these topics are published on 

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