Data Vault 2.0 using Databricks Lakehouse Architecture on Azure
This Article is about Data Vault 2.0 using Databricks Lakehouse Architecture on Azure and is presented in partnership with VaultSpeed and Scalefree our Microsoft Partner Network on Data Warehouse Automation and is part of Blog series. Please see the Landing Page here for more Articles. This Article is Authored By Jonas De Keuster & Koen Moermans from VaultSpeed and Co-authored with Michael Olschimke, co-founder and CEO at Scalefree International GmbH The Technical Review is done by Ian Clarke, Naveed Hussain, Irfan Maroof and Hajar Habjaoui – GBBs (Cloud Scale Analytics) for EMEA at MicrosoftData Vault 2.0 Modelling in Synapse Data Warehouse on Microsoft Fabric
The previous articles of this blog series discussed the Data Vault 2.0 architecture and methodology. The next articles will focus on another Data Vault 2.0 pillar: the Data Vault 2.0 model. The model has been developed specifically for enterprise data warehousing. It is an extensible model that can deal with structural changes in the data and can be extended over time by additional data (and business logic). Therefore, it fits well into agile methodologies such as Scrum. The model is also the basis for the automation capabilities of the Data Vault 2.0 approach. Software packages such as Vaultspeed rely on these patterns to generate the model in a data-driven approach. This helps enterprises to manage data flows at scale.
