Aug 23, 2024 · In Data Vault 2.0, the recommended approach to model transactions, events or, in general, non-changing data is to utilize Non-historized Link entities - a.k.a. Transactional Link, discussed in our previous article to advanced Data Vault modeling.

May 23, 2024 · Data Vault is a data modeling methodology that focuses on three key pillars: flexibility, scalability, and resilience. It is designed to handle large volumes of data from a variety of sources...

Jun 30, 2023 · The foundation for this framework is the Data Vault 2.0 System of Business Intelligence. This article presents the Data Vault 2.0 reference architecture based on data lakes and we discuss how we implement it on the Microsoft Azure cloud.

Jun 30, 2023 · In this article, we take a high-level look at how Data Vault 2.0 can be applied to the Databricks platform. Delta lake gives us an open-source storage layer on top of cloud data lake storage, like Azure data lake storage.

Discover the essentials of Data Vault 2.0 and its groundbreaking modeling techniques for scalability. Unlock the power of data vault modeling. Dive in now!

Dec 28, 2023 · Data Vault 2.0 is a data modelling methodology and system architecture that is specifically designed to address the challenges of managing and integrating large volumes of data in a...

Data Vault Anti-pattern: Using Historized Links to store Transactional data that does not change

Home of Data Vault 2.0 and Dan Linstedt, inventor of Data Vault, a complete Business Intelligence Solution. Get CDVP2 certification & training, and more.

Jan 19, 2022 · With the ever-changing landscape of source systems, modeling requirements, and data acquisition and integration options, the Data Vault 2.0 model provides the necessary patterns to adapt to...

Dive into the nuts and bolts of Data Vault 2.0. Learn about Data Vault's Three Pillars: Architecture, Model and Methodology and how to apply them.