Data Warehousing and Data Mining for Telecommunications (Artech House Computer Science Library) [Hardcover]

Rob Mattison (Author)

Book Description

Publication Date: August 1997 | Series: Artech House Computer Science Library

This book's in-depth analysis helps you understand how to engineer and implement a warehouse/mining strategy that reduces costs, maximizes profits, and supports long-term corporate goals. Providing new insights and knowledge-based management approaches, it helps you build a telecommunications data warehouse, develop the business case for financing system deployment, use mining tools to solve problem sets, and organize your warehousing effort.

Product Details

• Hardcover: 273 pages
• Publisher: Artech House (August 1997)
• Language: English
• ISBN-10: 0890069522
• ISBN-13: 978-0890069523
• Product Dimensions: 9.3 x 6.3 x 0.8 inches
• Shipping Weight: 1.2 pounds (View shipping rates and policies)
• Average Customer Review: 2.8 out of 5 stars  See all reviews (4 customer reviews)
• Amazon Best Sellers Rank: #2,939,743 in Books (See Top 100 in Books)

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Customer Reviews

Most Helpful Customer Reviews

4 of 4 people found the following review helpful:

3.0 out of 5 stars Entertaining and singular perspective of DW/DM in Telecoms, August 9, 1999

By 

Martyn Richard Jones "Martyn Richard Jones" (Cordoba, Spain) - See all my reviews
(REAL NAME)   

This review is from: Data Warehousing and Data Mining for Telecommunications (Artech House Computer Science Library) (Hardcover)

Hello Amazon,

The author, who has written extentsively on the subjects of DW and DM is also associated with Sequent Computer Systems, a respected manufacturer and vendor of high-end Enterprise Data Centers, and a highly experienced player in the DW, CRM, DSS space.

So, although I wouldn't discourage anyone interested in DW/DM in Telcos to read this book I would not do so with the previso that this is a perspective of data warehousing and data mining in Telecoms, and that there will be a divergence of opinion with a number of Mr. Mattisons observations, facts and experiences.

There is technology bias in most books that touch on the subjects (of Telcos, Data Warehousing and Data Mining), however this is pretty standard, alomost unavoidable and not necessarily undesirable if we take such accounts as one of a number of perspectives on the subject(s).

Although I didn't find the conenction between DW and KM to be too convincing, or the DW development strategy one that I would concur with, I would say that the attempt to identify the Telco value chain to be very well articulated.

So yes, if you are interested in the subject then go ahead and read it, but don't forget to put what you get from it in context - with the other diverse opinions on DW/DM and Telecoms - not too mention a lot of dramatically differing opinions regarding Knowledge Management.

Best regards,

Martyn R Jones

4 of 4 people found the following review helpful:

1.0 out of 5 stars Sales Collateral on software, March 17, 1999

By A Customer

This review is from: Data Warehousing and Data Mining for Telecommunications (Artech House Computer Science Library) (Hardcover)

I dont know who hired Rob Mattison to write this book. The first introduction on the Telco industri is ok and quite interesting but then the next ten chapters is the cleanest sales material from various software vendors. You will get far more value if you contact the vendors directly

2.0 out of 5 stars The definition of data mining is bizarre, June 9, 1999

By A Customer

This review is from: Data Warehousing and Data Mining for Telecommunications (Artech House Computer Science Library) (Hardcover)

Contrary to the previous review, the marketing stuff begins from chapter 7. One particular note: I found author's definition of data mining (p.18) strange at least: "Data mining tools is the category of software that includes any and all tools that, when provided to end users, give them the ability to do ad-hoc and/or user-defined analyses of information in order to solve specific business problems." Defining the topic that way, the author manages to describe MS Query as data mining tool. Some general architectural issues are valid and interesting, though.