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The Data Vault was invented by Dan Linstedt at the U.S. Department
of Defense, and the standard has been successfully applied to data
warehousing projects at organizations of different sizes, from
small to large-size corporations. Due to its simplified design,
which is adapted from nature, the Data Vault 2.0 standard helps
prevent typical data warehousing failures. "Building a Scalable
Data Warehouse" covers everything one needs to know to create a
scalable data warehouse end to end, including a presentation of the
Data Vault modeling technique, which provides the foundations to
create a technical data warehouse layer. The book discusses how to
build the data warehouse incrementally using the agile Data Vault
2.0 methodology. In addition, readers will learn how to create the
input layer (the stage layer) and the presentation layer (data
mart) of the Data Vault 2.0 architecture including implementation
best practices. Drawing upon years of practical experience and
using numerous examples and an easy to understand framework, Dan
Linstedt and Michael Olschimke discuss: How to load each layer
using SQL Server Integration Services (SSIS), including automation
of the Data Vault loading processes. Important data warehouse
technologies and practices. Data Quality Services (DQS) and Master
Data Services (MDS) in the context of the Data Vault architecture.
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