Data Vault Modeling Approach

In the Data Warehouse environment, there are two well-known modeling approaches according to Kimball and Inmon that have been used for countless years when it comes to storing data. However, these have to face more and more growing challenges:

It is therefore questionable whether these approaches are still appropriate for all the modern issues and requirements of today. This consideration gave rise to the Data Vault modeling approach.

The Data Integration Architecture of the Data Vault approach has robust standards and definition methods that bring information together to use them in a way that makes sense. The model consists of three basic table types:

Due to the structure and the defined standards, there are many advantages for the Data Vault approach:

• Massive reduction in development time when implementing business requirements
• Earlier return on investment (ROI)
• Scalable Data Warehouse
• Traceability of all data back to the source system
• Near-real-time loading (in addition to classic batch run)
• Big Data Processing (>Terabytes)
• Iterative, agile development cycles with incremental expansion of the DWH
• Few, automatable ETL patterns