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Data Integration Blueprint and Modeling: Techniques for a Scalable and Sustainable Architecture (IBM Press) Hardcover – January 6, 2011

ISBN-13: 978-0137084937 ISBN-10: 0137084935 Edition: 1st

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Product Details

  • Series: IBM Press
  • Hardcover: 416 pages
  • Publisher: IBM Press; 1 edition (January 6, 2011)
  • Language: English
  • ISBN-10: 0137084935
  • ISBN-13: 978-0137084937
  • Product Dimensions: 9.1 x 7.2 x 1 inches
  • Shipping Weight: 1.7 pounds
  • Average Customer Review: 4.4 out of 5 stars  See all reviews (5 customer reviews)
  • Amazon Best Sellers Rank: #1,181,812 in Books (See Top 100 in Books)

Editorial Reviews

About the Author

Anthony Giordano is a partner in IBM’s Business Analytics and Optimization Consulting Practice and currently leads the Enterprise Information Management Service Line that focuses on data modeling, data integration, master data management, and data governance. He has more than 20 years of experience in the Information Technology field with a focus in the areas of business intelligence, data warehousing, and Information Management. In his spare time, he has taught classes in data warehousing and project management at the undergraduate and graduate levels at several local colleges and universities.


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Customer Reviews

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Most Helpful Customer Reviews

7 of 9 people found the following review helpful By Dimitri K on October 28, 2012
Format: Hardcover Verified Purchase
The book is written in a vague unclear language, full of professional terms. Probably that's the language which professionals speak in their phone conferences. But professionals needn't read this book. And those terms are either not defined at all, or defined vaguely, as hints. Written this way, the book is written not for novices and students, but for colleagues, to show how clever the author is.

Here is the example: "Leveraging subject area files as a layer of conformance to a common file format that occurs on extract, plus changes that may occur in the target, such as collapsing tables, are shielded from the extract and transformation logic". And please note, that neither of those clever words are explained in the book. Enjoy reading.
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3 of 4 people found the following review helpful By T. Anderson TOP 1000 REVIEWERVINE VOICE on December 9, 2011
Format: Hardcover
Data integration is a complex, detailed, sometimes excruciating boring activity, which is not an activity for the light at heart.

This book does a great job of digging into the details of the data transformations. It is not just a high level look at data integration, it gets into the weeds.

The book is broken down into three parts. I have listed them and the chapters they contain below.

Part 1 Overview of Data Integration - Types of Data Integration, An Architecture for Data Integration, A Design Technique: Data Integration Modeling, and Case Study: Customer Loan Data Warehouse Project.

Part 2 The Data Integration Systems Development Life Cycle - Data Integration Analysis , Data Integration Analysis Case Study, Data Integration Logical Design, Data Integration Logical Design Case Study, Data Integration Physical Design, Data Integration Physical Design Case Study, Data Integration Development Cycle, and Data Integration Development Cycle Case Study.

Part 3 Data Integration with Other Information Management Disciplines - Data Integration and Data Governance, Metadata, and Data Quality.

It also includes four appendices - Exercise Answers, Data Integration Guiding Principles, Glossary, Case Study Models.

The thing I like most about this book is the way the authors follow each new topic chapter with a case study chapter. They introduce the theory and best practices and then they bring that to life through a real world case study.

Another thing I like about the book is that it is down to earth and very realistic. I have recently been on a MDM project. There are a lot misleading resources out there. The same can be said for data integration.
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1 of 2 people found the following review helpful By Sunil Soares on March 22, 2011
Format: Hardcover
I read this book end-to-end. It is a terrific practitioner's guide for anybody who is engaged with developing a large-scale data integration environment.

I have met with Tony personally as well, and he has a lot of credibility with clients, all of which flows through into this excellent book.

Well done Tony!

Sunil Soares
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0 of 2 people found the following review helpful By Data Guy on August 8, 2013
Format: Hardcover
Data Integration Blueprint and Modeling: Techniques for a Scalable and Sustainable Architecture by Anthony Giordano offers a consistent methodology and practices for integrating data across multiple sources and locations. With today's business focus on gleaning information via analytics on big data sets, it becomes increasingly necessary to focus on data integration techniques. And Giordano's book provides a wealth of knowledge on the subject.

The book is divided into three sections. The first section delivers an overview of data integration including a discussion of the types of data integration (EAI, SOA, ETL, etc.) and outlines a reference architecture for data integration. The second section of the book covers the data integration systems development lifecycle in detail. Each component of the lifecycle is defined and described and a case study using the lifecycle is presented. Finally, in the third section, Giordano discusses data integration in the context of other information management disciplines, including data governance, metadata, and data quality.

If your organization is tackling data integration issues you can learn a lot about getting them under control by reading Anthony Giordano's Data Integration Blueprint and Modeling: Techniques for a Scalable and Sustainable Architecture.
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0 of 3 people found the following review helpful By SHOUKAT KHAN on March 7, 2013
Format: Kindle Edition Verified Purchase
Nice explanation of each stage of the generic Data Integration modelling that may or may not be used in Actual implementation of the types of DI developed using the various DI tools.

But does give each generic stage of DI's explanation. This can be applied to SaaS Cloud-to-SaaS Cloud; SaaS Cloud-to-On-Premise and On-Premise-to-SaaS Cloud data integration patterns for either the Real-Time Sync, Scheduled-Batch Sync or Initial Load Sync of DI project.

Great Read!
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