Data Vault
Data Vault 2.0 is the evolution of the standards for Data Vault. Before I go any further I think it is wise to state that Wikipedia needs an update, as it does not cover all of the components nor the full definition of Data Vault. To that end: here is the proper definition of “Data Vault” itself:Data Vault is a system of data warehousing and business intelligence that is comprised of three major components: the Data Vault Model, the Data Vault Methodology, and the Data Vault Systems Architecture.
Changes to the standard:
Data Vault 2.0 brings to the table improvements in the following areas:
Data Vault Modeling – changes have been made to adapt better performance levels for both loading and querying. These changes are also specific to ensuring the success of Data Vault Modeling with the use of NoSQL environments in a seamlessly integrated fashion.
Data Vault Methodology – while I’ve introduced bits and pieces of the methodology (such as implementation rules and procedures) during older certification classes, I’ve not really published in full, the complete components around the methodology. Data Vault 2.0 brings the full methodology to bear on the projects to ensure CMMI Level 5 compliance (which relies also on people’s ability to execute), TQM (overall for BI), Six Sigma (for project based build outs), and Agile for rapid 2 to 3 week delivery cycles. Data Vault 2.0 certification will require knowledge of the methodology as well as knowledge of the Modeling components.
Data Vault Architecture – In my book: Super Charge Your Data Warehouse I outline some of the systems architecture components necessary to make the “Data Vault System” a success. In Data Vault 2.0 not much has changed here, with the exception being: the inclusion of NoSQL environments for multiple purposes. Data Vault 2.0 certification will require knowledge of the NoSQL environments from both an architectural perspective, as well as an implementation perspective.