Building a Scalable Data Warehouse with Data Vault 2.0

by Daniel Linstedt, Michael Olschimke

Overview

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.

Product Details

ISBN-13:	9780128025109
Publisher:	Elsevier Science
Publication date:	09/29/2015
Edition description:	New Edition
Pages:	688
Product dimensions:	7.50(w) x 9.00(h) x 1.30(d)

About the Author

Dan Linstedt has more than 25 years of experience in the Data Warehousing and Business Intelligence field and is internationally known for inventing the Data Vault 1.0 model and the Data Vault 2.0 System of Business Intelligence. He helps business and government organizations around the world to achieve BI excellence by applying his proven knowledge in Big Data, unstructured information management, agile methodologies and product development. He has held training classes and presented at TDWI, Teradata Partners, DAMA, Informatica, Oracle user groups and Data Modeling Zone conference. He has a background in SEI/CMMI Level 5, and has contributed architecture efforts to petabyte scale data warehouses and offers high quality on-line training and consulting services for Data Vault.

Michael has more than 15 years of experience in IT and has been working on business intelligence topics for the past eight years. He has consulted for a number of clients in the automotive industry, insurance industry and non-profits. In addition, he has consulted for government organizations in Germany on business intelligence topics. Michael is responsible for the Data Vault training program at Dörffler + Partner GmbH, a German consulting firm specialized in data warehousing and business intelligence. He is also a lecturer at the University of Applied Sciences and Arts in Hannover, Germany. In addition, he maintains DataVault.guru, a community site on Data Vault topics.

Table of Contents

Chapter 1. Introduction to Data WarehousingChapter 2. Scalable Data Warehouse ArchitectureChapter 3. The Data Vault 2.0 MethodologyChapter 4. Data Vault 2.0 ModelingChapter 5. Intermediate Data Vault ModelingChapter 6. Advanced Data Vault ModelingChapter 7. Dimensional ModelingChapter 8. Physical Data Warehouse DesignChapter 9. Master Data Managment Chapter 10. Metadata Managment Chapter 11. Data ExtractionChapter 12. Loading the Data Vault Chapter 13. Implementing Data Quality Chapter 14. Loading the Dimensional Information MartChapter 15. Multidemensional Database

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From the Publisher

This book covers everything users need to create a scalable data warehouse from scratch, including a presentation of the Data Vault modeling technique which provides the foundations to create a technical data warehouse layer, also including tactics on how to create the inner and presentation layer of the data vault 2.0 standard.