Contrasting Data Mesh with Data Vault highlights tensions between decentralised ownership and structured enterprise modelling in modern data architectures.

Torsten Glunde explored the compatibility of Data Vault and Machine Learning in a model-driven architecture, emphasising the automation and operationalisation potential for machine learning models, including feature management, algorithms, parameters, and training scores.

Dylan Roe presented a case study showcasing how Osiris Trading adopted and learned Data Vault. The presentation detailed the challenges faced during the implementation and provided insights into the status of the project.

This session explores Data Vault performance on Snowflake, focusing on constraints, design choices, and optimisation strategies for scalable cloud data models.

Jennifer Stirrup presented the question, “Is your Data your Organisational North Star or Death Star?” Many businesses grappled with the transition from static reports to innovative analytics and are struggling to adapt. They have also recognised that implementing Business Intelligence projects demanded a different skill set and a shift in organisational culture. This presentation unveiled some of those answers.

Mustafa Rhemtulla presented a case study on Oodle Car Finance’s experience in implementing Data Vault.

Neil Sparrow explained integrating Kimball models with Data Vault, emphasising its role in preventing data silos and enabling incremental development. He touched on Data Vault architecture and innovative team concepts.

Richard Adams discussed gaining senior leadership support for Data Vault initiatives, the “7 Steps to Maximise Data Value,” and business user perspectives on Data Vault initiatives.

This session shows how automation can simplify Data Vault modelling and speed up delivery while maintaining structure and consistency across projects.

Petr Beles, CEO of Datavault Builder, discussed simplifying Data Warehouse projects and achieving maintainability. He emphasised the importance of the business data model as the foundation for Data Vault-driven data warehousing.

Francesco Puppini highlighted the benefits of using the Unified Star Schema (USS) in building an Information Mart. He presented an alternative approach for handling large data volumes and included a live demo.

Jean-Francois Saluden and Stephane Vivien addressed the challenge of managing evolving business keys within business process. They discussed scenarios where business keys were constructed during processes, leading to multiple contact keys in the Data Vault system. The session explored strategies to consolidate these keys into a unified one.

Alessia Pulieri shared the transformation journey from an outdated Data Warehouse to a scalable, flexible Data Vault 2.0 Enterprise Data Warehouse achieved through agile practices and strategic partnerships.