Building a Scalable Data Warehouse with Data Vault 2.0 (英语) 平装 – 2015年10月13日
Dan 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.
Chapter 1. Introduction to Data Warehousing Chapter 2. Scalable Data Warehouse Architecture Chapter 3. The Data Vault 2.0 Methodology Chapter 4. Data Vault 2.0 Modeling Chapter 5. Intermediate Data Vault Modeling Chapter 6. Advanced Data Vault Modeling Chapter 7. Dimensional Modeling Chapter 8. Physical Data Warehouse Design Chapter 9. Master Data Managment Chapter 10. Metadata Managment Chapter 11. Data Extraction Chapter 12. Loading the Data Vault Chapter 13. Implementing Data Quality Chapter 14. Loading the Dimensional Information Mart Chapter 15. Multidemensional Database
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I've read the Supercharge Your Data Warehouse book from Dan, I've read all of Hans Hultgren's books, I've read and watched DV fundamentals training material, and I never really felt like I fully understood everything end to end. I grasped the big picture and was excited about the possibilities, but working alone after all of that I felt like I still didn't really have the tools I needed to complete a data vault on my own. With this book, I finally do!
This book takes you from concepts to implementation, from beginning to end. There are actual screen shots of how to create databases, what indexes to put on your vault tables, how to create an SSIS package, TSQL code, Master Data Services and Data Quality Services examples, there's MDX code, all of it. And it's not just details to get you to a data vault and then leaving you on your own to figure out the info marts, this takes you all the way to putting data in your dimension and fact tables.
All in all, this is the most complete Data Vault book that's ever been created and it's a fantastic value for the money. It's like 684 pages. Once I started, it was literally 8 hours a day for 4-5 days of plowing through all the information and going back and re-reading and getting more details out of it before I was done. It's not a book you can just flip through in a couple of hours. I HIGHLY recommend this book for anyone interested in data vault or data warehousing in general.
Using the MD5 haskey is brilliant since it creates a unique 32 character surrogate key based upon the business key(s) phrase which documents the how the haskey was created. I am going to leverage it in PowerPivot which requires a singular key for BISM relationships and if the business keys change so will the hashkey.
As per Number2 , This book takes you from concepts to implementation, from beginning to end. There are actual screen shots of how to create databases, what indexes to put on your vault tables, how to create an SSIS package, TSQL code, Master Data Services and Data Quality Services examples, there's MDX code, all of it. And it's not just details to get you to a data vault and then leaving you on your own to figure out the info marts, this takes you all the way to putting data in your dimension and fact tables.
I would probably move chapter 3 to the end of the book and treat it as a bonus where the rest of the book is the meat and potatoes that made us purchase it. I Also HIGHLY recommend this book for anyone interested in data vault or data warehousing in general.
There are many examples using SSIS to implement the Data Vault. These did not apply to me as I am implementing it in Hadoop/Hive, so I cannot speak to their efficacy. I do wish there was more documentation out there on details of implementing the Data Vault using Hadoop, but even web resources are limited.
Overall I highly recommend this book to anyone who is interested in Data Vault.