Building a scalable data warehouse with data vault 2.0

The Data Vault, created by Dan Linstedt at the U.S. Department of Defense, has been effectively implemented in data warehousing projects across various organizations. Its nature-inspired, simplified design helps mitigate common data warehousing failures. This resource provides comprehensive guidance on building a scalable data warehouse from start to finish, focusing on the Data Vault modeling technique that underpins a technical data warehouse layer. It emphasizes an incremental approach using the agile Data Vault 2.0 methodology. Readers will learn to construct both the input layer (stage layer) and the presentation layer (data mart) within the Data Vault 2.0 architecture, along with best practices for implementation. Drawing from extensive practical experience, the authors present numerous examples within an accessible framework. Key topics include loading each layer using SQL Server Integration Services (SSIS) and automating Data Vault loading processes. The book also covers essential data warehouse technologies, Data Quality Services (DQS), and Master Data Services (MDS) in relation to the Data Vault architecture. It offers a thorough introduction to data warehousing, blending theoretical concepts with hands-on instruction, while demystifying data vault modeling through various techniques. Additionally, it highlights the advantages of the data vault approach over other methods, including updates and enhancements to Data V