File Size: 5228 KB
Print Length: 528 pages
Publisher: Wiley; 1 edition (December 10, 2007)
Publication Date: December 10, 2007
Given that this book was written more than ten years ago, many things have changed and an up-date is desparately needed., Will be certainly a lot of info here and it sums to a college or university text message. It's very in depth and will require as much time as any college or university text would. Several chapters stand out like Cleansing and Conforming. Metrics development is discussed in depth in ways that may have been overlooked in other text messaging like here. The examples go very deep into generation of surrogate keys, mass loading of Type 1s, minimum key requirements in dimensions and other ETL concepts with regards to the error review table. The book was written very obviously from practical situations encountered in daily work.
The book does not present or attempt to develop the " Kimball Method" of SCD. As it turns out, that's far less important than all of those other things required simply to execute a day's ETL cycle for which much may go wrong. Numerous tips are worked into this text. That seems that the small things add up greatly throughout a review of the book. For example , it's a mistake to allow NULLs actually to be the prime indicator for an active Type 2 record specifically because a simple SQL call needing a date range manipulated by BETWEEN will fail if the active indicator is NULL. It's the fine points similar to this that rate this book very highly.
This is not a trivial one-time-only to read book. It appears that this sort of planning should be a little more in facts in a lot of the shops. Let's face it. IT but especially ETL is a high conclusion engineering self-discipline, more so with EDW.
As far as criticisms are concerned, the SQL examples are good but are PL/SQL and require time for you to decode for those building in MSSQL environments. Typically the book was written in 2002 when Oracle was the main player and there was not so many Teradata shops. That may make the book too again level for some visitors. However, the book includes nearly all of the subject issue with no specific implementation specifics, enough so that the key concepts works irrespective of the technology chosen.
It's not very likely that a course like here would even be taught at a college or university level and therefore the book is a vital investment. Further, this book could be used for two full semesters, dependent on this reviewer's experience in official course work. It's not likely that on-the-job training would supplant the need for the ability included in this book or one like it., We have been doing this for 9 years, and this is the best book I've seen on ETL procesing and its role in data warehousing. Before you start your data warehouse effort have your team read this book. Not just the ETL members... both the front/back room technicians will benefit from understanding the clear presentation of what can be in scope (dare We say, "best practice" yikes! ) for ETL processing. The delete word capturing highly valuable data quality and cleansing processes is no less helpful than the emphasis on loading the data unless it is deceiving enmasse or so certainly flawed. The bias toward driving the data to the front room for presentation forces data quality issues to the area where they must be dealt with and the loop to operational systems (or perhaps even flawed ETL transforms! ) closed. Illustrates alternatives to relieve symptoms of the messy reality of suspended data, late arriving facts and dimensions. Use it as a guide for your ETL efforts. Acquire this book, read it and then get a few more for your team if you agree., This is apparently a good book but I would not suggest getting the kindle version as I am not able to view the diagrams in the kindle they are way too small and are not able to be resized. You skip key information from not being able to view the diagrams. Apart from this I would recommend the book, just not the kindle version. I use the Black and white Kindle, not the new Kindle Fire. Uncertain if that makes a difference., Ralph Kimball has rounded away his complete recipe for building fast, cost effective, robust and durable organization dimensional data warehouses with this immensely valuable addition to all IT & Data Warehouse professionals' bookshelves.
Without a doubt ETL has been the biggest stumbling obstruct to deploying and maintaining well architected data facilities that stand the test of time. Ralph pulls on his years of experience and engagement with thousands of projects and crystallizes the `Best Practices' into an efficient application structures for all ETL systems regardless of the tools projects use for implementation.
In this thorough examination of the Remove, Transform and Load (ETL) process, Ralph identifies 38 critical functions that every ETL systems need to implement for success in a long time. He thoughtfully lays out simple and practical approaches for how each of these functions can be implemented by projects with any size of budget.
With regard to many, the paradoxical character of ETL (seeming trivial yet replete with endlessly complex details that constantly change) has been the proverbial straw that has broken the lender for many DW projects. Continual customer pressure to grow, improve performance, and quickly offer with changing business conditions have left developers and architects grasping for more powerful and flexible approaches to ETL that meet project timelines, yet evolve and improve with age. Provided with this enlightening roadmap, many DW professionals will be far better outfitted to develop and build systems that satisfy the challenges today and tomorrow., This is a good book to study from and it will not assume anything, and matters are presented plainly. I am not finished with the book yet (due to lack of time), but I am glad I got the book., Can't make clear how helpful this book is for data engineers. Really a great read and one of my top suggested books
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