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Data Modeling for the Business: A Handbook for Aligning the Business with IT using High-Level Data Models (Take It with You Guides) [Paperback]

Steve Hoberman , Donna Burbank , Chris Bradley , Mona Pomraning
4.7 out of 5 stars  See all reviews (6 customer reviews)

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Book Description

March 25, 2009 Take It with You Guides
Did you ever try getting Businesspeople and IT to agree on the project scope for a new application? Or try getting Marketing and Sales to agree on the target audience? Or try bringing new team members up to speed on the hundreds of tables in your data warehouse - without them dozing off?

Whether you are a businessperson or an IT professional, you can be the hero in each of these and hundreds of other scenarios by building a High-Level Data Model. The High-Level Data Model is a simplified view of our complex environment. It can be a powerful communication tool of the key concepts within our application development projects, business intelligence and master data management programs, and all enterprise and industry initiatives.

Learn about the High-Level Data Model and master the techniques for building one, including a comprehensive ten-step approach and hands-on exercises to help you practice topics on your own. In this book, we review data modeling basics and explain why the core concepts stored in a high-level data model can have significant business impact on an organization. We explain the technical notation used for a data model and walk through some simple examples of building a high-level data model. We also describe how data models relate to other key initiatives you may have heard of or may be implementing in your organization.

This book contains best practices for implementing a high-level data model, along with some easy-to-use templates and guidelines for a step-by-step approach. Each step will be illustrated using many examples based on actual projects we have worked on. One example spans an entire chapter and will allow you to practice building a high-level data model from beginning to end, and then compare your results to ours. Building a high-level data model following the ten step approach you will read about is a great way to ensure you will retain the new skills you learn in this book.

As is the case in many disciplines, using the right tool for the right job is critical to the overall success of your high-level data model implementation. To help you in your tool selection process, there are several chapters dedicated to discussing what to look for in a high-level data modeling tool and a framework for choosing a data modeling tool, in general.

This book concludes with a real-world case study that shows how an international energy company successfully used a high-level data model to streamline their information management practices and increase communication throughout the organization - between both businesspeople and IT.

Data modeling is one of the under-exploited, and potentially very valuable, business capabilities that are often hidden away in an organizations Information Technology department. Data Modeling for the Business highlights both the resulting damage to business value, and the opportunities to make things better. As an easy-to follow and comprehensive guide on the why and how of data modeling, it also reminds us that a successful strategy for exploiting IT depends at least as much on the information as the technology.
Chris Potts, Corporate IT Strategist and Author of fruITion: Creating the Ultimate Corporate Strategy for Information Technology

The authors of Data Modeling for the Business do a masterful job at simply and clearly describing the art of using data models to communicate with business representatives and meet business needs. The book provides many valuable tools, analogies, and step-by-step methods for effective data modeling and is an important contribution in bridging the much needed connection between data modeling and realizing business requirements.
Len Silverston, author of The Data Model Resource Book series


Frequently Bought Together

Data Modeling for the Business: A Handbook for Aligning the Business with IT using High-Level Data Models (Take It with You Guides) + Data Modeling Made Simple: A Practical Guide for Business and IT Professionals, 2nd Edition + MASTER DATA MANAGEMENT AND DATA GOVERNANCE, 2/E
Price for all three: $108.91

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Editorial Reviews

About the Author

About Steve
Steve Hoberman is a world-recognized innovator and thought-leader in the field of data modeling. He has worked as a business intelligence and data management practitioner and trainer since 1990. He is the author of Data Modelers Workbench and Data Modeling Made Simple, the founder of the Design Challenges group and the inventor of the Data Model Scorecard®.

About Donna
Donna Burbank has a unique perspective on the field of data modeling - having helped design and produce several of the leading metadata and data modeling tools in the market today, as well as having spent many years as a consultant implementing these solutions. As a consultant, she has worked with Global 2000 companies worldwide and as a software provider, she has been instrumental in the development efforts at Platinum Technology, Embarcadero Technologies, and CA.

About Chris
Christopher Bradley has spent almost 30 years in the field of Information Management working on Master Data Management, Enterprise Architecture, Metadata Management, Data Warehouse and Business Intelligence implementations. Currently, Chris heads the Business Consultancy practice at IPL, a UK based consultancy.


Product Details

  • Paperback: 288 pages
  • Publisher: Technics Publications, LLC; First edition (March 25, 2009)
  • Language: English
  • ISBN-10: 0977140075
  • ISBN-13: 978-0977140077
  • Product Dimensions: 10.2 x 0.7 x 7.1 inches
  • Shipping Weight: 1.3 pounds (View shipping rates and policies)
  • Average Customer Review: 4.7 out of 5 stars  See all reviews (6 customer reviews)
  • Amazon Best Sellers Rank: #522,331 in Books (See Top 100 in Books)

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4.7 out of 5 stars
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Most Helpful Customer Reviews
10 of 10 people found the following review helpful
3.0 out of 5 stars Review from Oil IT Journal -[...] April 22, 2010
Format:Paperback|Amazon Verified Purchase
Review--Data Modeling for the Business (March 2010) - review originally appeared in Oil IT Journal - [...].

Oil IT Journal reviews `Data Modeling for the Business' by Steve Hoberman et al. The book outlines a new approach to data modeling and includes a chapter on a major oil company's enterprise architecture.

Someone once said the ideal number of data modelers is one. The book `Data Modeling for the Business' (DMFTB) takes practically the opposite approach, advocating a series of corporate Rolfing sessions and pizza parties to thrash out what should be modeled, how, and for how long information should be retained. If the single modeler approach presupposes a domain specialist who knows all, Hoberman's is rather of journeymen data modelers, perhaps without deep domain knowledge, who can extract all the information required from other stakeholders. The thrust of DMFTB is communication and debate with non specialists. This can be rather labored--as in the first chapter which plods through the analogy of a data model and a blueprint for a house.

Those expecting technology insights and a discussion of tools will be disappointed. We learn from the frontispiece that the graphical models in the text were created with CA's ERwin tool. But the book does not really connect with technology. The subtitle of `aligning business with IT using high level data models' says it all.' This discussion is far removed from databases and SQL and focuses on a bird's-eye view of the enterprise rather than on implementation.

There are `traditionally' four levels of models--very high, high, logical and physical. High level models communicate core data concepts like `customer,' `order,' `engineering,' `sales.' Even the `logical' is model is `a graphical representation of [...] everything needed to run the business.' All of which is a far cry from the Express logical model of Epicentre or ISO 15926!

The body of DMFTN is concerned with business, rather than technical data, examining in depth how for instance the concept of `customer' can be implemented in `hundreds of database tables on a variety of platforms.' Business requirements may mean changing definitions of key concepts like customer. These start at the high level, and ripple down through the model layers. Modelers can then perform impact analysis to see `what changes are required at the logical and physical levels.' Although how such changes are effected across `hundreds' of databases including pre-packaged behemoths like SAP is glossed over.

Of particular interest is a chapter on data modeling in an international energy company. Here an enterprise architecture initiative set out with a vision of a `shared corporate data asset that is easily accessible.' Amusingly, half way through their work, the team found that there was another initiative working on master data management whose goal was also `a single version of the truth.' Such is the nature of the large decentralized beast! The oil company's modelers leveraged industry data models including PPDM, PSDM (ESRI), MIMOSA and PRODML--although exactly how these different circles were squared is not explained!

Despite its technical weakness, DMFTB makes an interesting and perhaps inspiring read for technologists who are trying to engage with their fellow stakeholders.

Comments to info@oilit.com.
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9 of 9 people found the following review helpful
5.0 out of 5 stars A necessary start to any modeling journey May 11, 2009
Format:Paperback
Good handbook on Data Modeling High Level or Conceptual Data Model. The emphasis is on starting out with clear and concise High Level Data Models, which closely match the business requirements. Very useful book that not only gives you best practices but leaves you with a step-by-step methodology you could start using immediately. The book has a good flow with excellent illustrations, examples and case studies.
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6 of 7 people found the following review helpful
Format:Paperback
One of the most critical systems issues is aligning business with IT and fulfilling business needs using data models. The authors of "Data Modeling for the Business" do a masterful job at simply and clearly describing the art of using data models to communicate with business representatives and meet business needs. The book provides many valuable tools, analogies, and step-by-step methods for effective data modeling and is an important contribution in bridging the much needed connection between data modeling and realizing business requirements.
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