Building a Scalable Data Warehouse with Data Vault 2.0

Informationen zum Autor 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. Klappentext Building a Scalable Data Warehouse with Data Vault 2.0 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. In addition, the book presents tactics on how to create the input layer (the stage layer) and the presentation layer (data mart) of the Data Vault 2.0 standard. Drawing upon years of practical experience and using numerous examples and an easy to understand framework, Dan Listedt and Michael Olschimke discuss tactics on 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, and data quality services (DQS) and master data services (MDS) in the context of the data vault architecture. Inhaltsverzeichnis 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 ...

Autorentext
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.

Klappentext
Building a Scalable Data Warehouse with Data Vault 2.0 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. In addition, the book presents tactics on how to create the input layer (the stage layer) and the presentation layer (data mart) of the Data Vault 2.0 standard. Drawing upon years of practical experience and using numerous examples and an easy to understand framework, Dan Listedt and Michael Olschimke discuss tactics on 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, and data quality services (DQS) and master data services (MDS) in the context of the data vault architecture.

Inhalt

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