The Data Vault Experience Workshop

Data Vault

Companies have long struggled with making their data warehouse resilient to change. While traditional data modeling approaches such as Kimball, Star schemas & Inmon are great for directly performing analytics, they have shown weaknesses when it comes to reacting to serious organizational changes. Retaining history properly and redesigning the schema can be challenging. Enter Data Vault! Data Vault is a methodology designed for data warehousing that focuses on flexibility, scalability, and agility in handling large volumes of data. At a high level, it employs three main types of entities: Hubs, Links, and Satellites. Hubs represent business entities, Links denote the relationships between these entities, and Satellites capture the context and history of the data. This approach enables a more robust and adaptable data architecture, accommodating changes in business requirements with ease while ensuring data integrity and traceability.

Practice makes perfect

We all know that learning a new skill is difficult, if you don’t get to apply your skills right away. Practice makes perfect. That’s why we have developed a dynamic and engaging workshop where participants can dive into the intricacies of Data Vault. This hands-on experience provides both learning and practical application, allowing attendees to gain firsthand insights into implementing and managing Data Vault structures. Whether you’re new to Data Vault or seeking to enhance your skills, join us for an enriching opportunity to explore this cutting-edge approach in a cool and fun environment. The first workshop of this kind will be run on April 23rd, 2024 in Düsseldorf. My team from Agile Data Engine will be joined by the great people from our trusted implementation partner INFORM DataLab. You can find more infos about this event on our Agile Data Engine home page.

Ready to learn more about Data Vault?

Why wait? You can register directly via the following form. (Please note that your data will be further processed by INFORM DataLab).