Data Mesh is the latest and much talked about data platform architecture to emerge. The Data Mesh approach is more broad-scoped than other methods out there, and deliberately doesn’t provide details of exactly how to build some of the components needed for a Data Platform solution.

It includes recommendations on data governance, data product management, federation, and self-service. It focuses on what a business needs to put in place for effective analytics, providing an architecture, and identifying the interfaces that components need to satisfy to make the architecture work.

It is early days yet, however, there has been a lot of industry interest and there are companies trying to implement a Data Mesh. For some of these, a Data Vault is part of the solution.

This presentation will assess the Data Mesh method and explain how a Data Vault can be used to underpin success.

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.

Alessia Pulieri shared the transformation journey from an outdated Data Warehouse to a scalable, flexible Data Vault 2.0 Enterprise Data Warehouse achieved through agile practices and strategic partnerships.

Patrick Cuba, one of the world’s leading thought-leaders on the use of Data Vault, and author of “The Data Vault Guru: A Pragmatic Guide on Building a Data Vault”, explains how to make your Data Vault sing using Snowflake’s unique Data Cloud Architecture.

The Snowflake Senior Solutions Architect shares different techniques and ideas that you could use in your own Data Vault, as well as exploring the new workshop he has developed, which contains add-on information regarding new features introduced by Snowflake.

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.

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.

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.

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.

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

Petr Beles, CEO of Datavault Builder addresses: the complexity of Data Warehouse projects, the problem of Data Warehouse implementations and provides insights on approaching complexity and maintainability.

Petr explains that the business data model is not only more constant over time but should be the foundation of your Data Vault driven data warehouse automation.

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.

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.