Start: Q4/2022
Publication: March 2023
Region: Global
A growing number of enterprises use the data vault approach for implementing data warehouses to support analytics projects in a scalable, predictable and consistent way. This approach excels at loading all your data, tracking history and changing schemas.
The data vault offers a hybrid approach to data modeling that seeks to capture the best and avoid the worst of earlier approaches. Dan Linstedt invented the data vault by combining elements of Ralph Kimball’s star schema model and Bill Inmon’s third-normal form, then adapting them to store all historical data and track changes over time. The data vault 2.0 standard codifies this approach and prescribes a methodology along with reference architectures for a range of physical environments, including a data warehouse, data lake, data fabric and data mesh.
This report by Eckerson Group and BARC assesses the scale, scope and nature of data vault adoption based on a survey of enterprise data practitioners across the globe. It will examine their motivations, obstacles, failures and successes—as well as their adherence to the data vault 2.0 standard.
Read this report to learn:
- The scale and scope of data vault adoption worldwide
- Why enterprises do or don’t adopt the data vault
- Benefits and challenges of implementing the data vault
- How enterprises learned about and implemented the data vault
- What use cases it addresses
- What lessons we can learn from their experience