Building a Scalable Data Warehouse with Data Vault 2.0Linstedt, Daniel, Olschimke, Michael By Dan Linstedt

TheData Vault was invented by Dan Linstedt at the US 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 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 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 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 discussHow 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 Provides a complete introduction to data warehousing, applications, and the business context so readers can get up and running fast Explains theoretical concepts and provides hands on instruction on how to build and implement a data warehouseDemystifies data vault modeling with beginning, intermediate, and advanced techniquesDiscusses the advantages of the data vault approach over other techniques, also including the latest updates to Data Vault and multiple improvements to Data Vault Building a Scalable Data Warehouse with Data Vault 2.0Linstedt, Daniel, Olschimke, Michael

Prompt delivery. As stated, Dan Linstedt This book is an excellent reference on how to use Data Vault in your Data Warehouse. Starting from the Architecture, explaining data vault modeling and then going into the details of loading. It covers all essential parts in depth and allows the reader to construct a data vault. In that regard it is way better than the earlier Super Charge Your Data Warehouse: Invaluable Data Modeling Rules to Implement Your Data Vault from Dan Linstedt.I have learned a lot from the book and I often come back to it, using it as the standard solution and evaluating specific questions about modelling or data vault architecture against it. Because I sometimes lend it and forget to whom, so I had to buy it several times â€" it is worth it. English I'm about half way through the book now. I think the core modelling concept in Data Vault is strong, flexible and valuable, hence my interest. This method solves many, but not all issues that say Kimball and Inmon don't. Crucially, it deals with the key issue of agility and that alone is worthwhile. This book takes the DV concept much further though and introduces many additional concepts such as how to run the project and manage the quality of data and processes. These aren't necessarily what a data modeller/architect would be interested in and it may be a challenge for them to suggest to their boss that they need to introduce TQM or Six Sigma to do DV2. However, the author(s) are trying to give a complete overview of their best practice. This could be seen as help for the inexperienced or stretching a really good idea too far. I would also make a number of other general observations. Firstly, I find that some of the writing could be better and it looks like the proof reading was a bit ropey. Second, effort is made explaining concepts that for many data architects will be basic skills/knowledge. I recall an example from one of Kimball's books that illustrates this and which this book also displays. Kimball introduces the idea of the 34 subsystems of ETL, one of which is the surrogate key manager. For many people, using SQL or modern RDBMS, this is just an identity setting on a column in a table. Yet, Kimball (and the others) spend nearly half a page explaining it, which could be argued to get in the way of the saying you need an identity generator. The other issue is that in any data, you will come across a problem, let's call it Problem X. All methods will say here's how we deal with Problem X.you use a ProblemXFixer. So basically, someone has to explain the problem and give the fix a name to fit it into their standard. In this book, entire chapters are given over to variations on the basic theme of Hubs, Links and Satellites when really, you could probably just bullet point each and say here's a few variations on the theme. So as with all such standards, many words are used when less could do the trick. Having said all of that, I think the core technique and experience on offer here is worth the effort and I'm off to finish the book. One final thingthe book is quite up to date with MS SQL Server and refers to it quite a lot. You may view that as good/bad depending on your skillset. Building a Scalable Data Warehouse with Data Vault 2.0Linstedt, Daniel, Olschimke, Michael Enjoyed: touches all data vault entities+ddl+loading.NOK bit outdated in some aspects as of 2022 where Data Vault practice changed some recommendations. I didn't appreciated the fact all examples using sql servers with screenshots of sql server or analysis server. I think a reference semantic book should had been agnostic of specific technology. 0128025107 If you would like to know about the concepts of Data Vault, don't buy this book.Even though one of its authors is Dan Linstedt (Mr. Data Vault himself), even though Dan said on his website that you should buy this book.As others have already commented: if you are particularly interested in lots of sql listings and pages of screenshots of how to do (very particular) things in ms sql server, then this is probably the book for you.But of course there is in this book and I am thinking of a random collection of buzzwords that seem to differentiate Data Vault2.0 from the old Data Vault concept. Maybe this is moderately useful for someone, for example to convince non technical stakeholders that you are doing the right thing.This book has not only disappointed me, it has also convinced me that DV2.0 is nothing than a heap of bI would probably think hard before buying any book from the same authors again.(Still Data Vault I mean without the 2.0 has its merits, but you if you want to know what it is about, you should simply follow the links in the wikipedia article to the original papers and from thereon just trust your common sense and not the celebrities) English