Data Modeling for the Business: A Handbook for Aligning the Business with IT using High-Level Data Models

Technics Publications
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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. Names have been changed to protect the innocent, but the pain points and lessons have been preserved. 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’ll 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 organization’s 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 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. Len Silverston, author of The Data Model Resource Book series
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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.
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Additional Information

Publisher
Technics Publications
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Published on
Apr 1, 2009
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Pages
288
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ISBN
9781634620437
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Best For
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Language
English
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Genres
Computers / Computer Graphics
Computers / Data Modeling & Design
Computers / Information Technology
Computers / Information Theory
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Content Protection
This content is DRM protected.
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This book provides you with a collection of best practices, guidelines, and tips for using the Unified Modeling Language (UML) for business analysis. The contents have been assembled over the years based on experience and documented best practices. Over sixty easy to understand UML diagram examples will help you to apply these ideas immediately. If you use, expect to use, or think you should use the Unified Modeling Language (UML) or use cases in your business analysis activities, this book will help you: • communicate more succinctly and effectively with your stakeholders including your software development team, • increase the likelihood that your requirements will be reviewed and understood, • reduce requirements analysis, documentation, and review time. The first three chapters explain the reasons for utilizing the UML for business analysis, present a brief history of the UML and its diagram categories, and describe a set of general modeling guidelines and tips applicable to all of the UML diagram types. Each of the next thirteen chapters is dedicated to a different UML diagram type: 1. Use Case Diagrams 2. Activity Diagrams 3. Interaction Overview Diagrams 4. Class Diagrams 5. Object Diagrams 6. State Machine Diagrams 7. Timing Diagrams 8. Sequence Diagrams 9. Communication Diagrams 10. Composite Structure Diagrams 11. Component Diagrams 12. Deployment Diagrams 13. Package Diagrams The next two chapters explain additional diagram types that are important for business analysts and that can be created using UML notation: • Context Diagrams using Communication diagram notation • Data Models using Class diagram notation These chapters are followed by a chapter that describes criteria for selecting the various diagram types. The final chapter presents a case study.
Ian is a Chief Information Officer (CIO) who is about to go on a journey of change - whether he likes it or not. He will be expected to explore, challenge and radically recast the complex, often hostile relationships that can exist between a business and the people in its Information Technology (IT) department. On the way, Ian, his Chief Executive Officer, Chief Financial Officer and other key stakeholders, experience a transformation in how a business needs to think about the value of its IT people and the work that they do. This results in some truly groundbreaking innovations in the scope and contribution of Ian’s role as CIO, the people that work for him and the strategy that he leads. Watch the characters in this extraordinary business novel as they meet the challenge, struggle and grow. Share in Ian’s transformation, and join the author in observing key messages as the adventure unfolds. Part entertaining novel and part enlightening textbook - FruITion takes the reader through a discovery process revealing indispensable messages about the next generation of strategies for Information Technology. - Jeremy Hall, Managing Director, IRM UK Strategic IT Training FruITion brings vividly to life the issues of being a CIO in todays corporate world and how IT, when properly integrated into the objectives of a business can drive massive value creation. His insights into how to win the engagement war and bring technology strategies alive for the non technical are absolutely spot on. - Steve Adams, COO and Managing Director for Card Services, Euronet Worldwide The modern CIO is to be seen as part of the business rather than a service provider to the business. Chris Potts is at the forefront of thinking that will put us all there if we act on his inspiration. - David Brown, CIO of Scottish Water More from the author, Chris Potts: The debate over the CIO role, and about the extent to which it should be about business or technology, is taking place in an increasing vacuum of strategic context. Some CIOs have abandoned strategy altogether, while others persevere with a traditional IT Strategy founded in the mindset of the mainframe era. Meanwhile, business managers and staff continue to develop their knowledge of technology and understanding of how to exploit it. There seems to be a presumption that the next-generation strategic purpose of the CIO will be an incremental step on from what has gone before – significant, maybe, but still incremental. What if the CIO’s new strategic context is not incremental but disruptive, requiring a very different mindset and skillset? And, most crucially, what if the corporate strategists – rather than the CIO community – are the ones deciding what context is? Their offer to the CIO: you can become one of the corporate strategists like us, but not with your traditional scope and approach to strategy. What does that offer look like and what does it mean for incumbent CIOs and the people who work for them?
Are you struggling to understand the data you need to support your business activities? Are you frustrated over data that don’t answer your questions or provide the wrong answers to your questions? Are you worried that your organization is not adequately supporting its citizens or customers? Are you concerned over civil or criminal liability for the quality and use of your data? If the answer to any of these questions is Yes, they you need to read Data Resource Understanding to help you and everyone in your organization thoroughly understand the data they need to support the business activities. Most public and private sector organizations have no formal method for thoroughly understanding the data needed to support their business activities. They seldom have a method that begins with the organization’s perception of the business world and continues through a formal Data Resource Development Cycle to produce a high quality, thoroughly understood data resource that fully supports the organization’s current and future business information demand. Data Resource Data provided the complete detailed data resource model for understanding and managing data as a critical resource of the organization. Data Resource Understanding is the companion book to Data Resource Data. It provides a detailed explanation of how to thoroughly understand an organization’s data resource and to document that understanding with Data Resource Data. Together they provide an organization with the foundation for properly managing their data as a critical resource. Like Data Resource Simplexity, Data Resource Integration, Data Resource Design, and Data Resource Data, Michael Brackett draws on over half a century of data management experience, in a wide variety of different public and private sector organizations, to understand and document an organization’s data resource. He leverages theories, concepts, principles, and techniques from many different and varied disciplines, such as human dynamics, mathematics, physics, chemistry, philosophy, and biology, and applies them to the process of formally documenting an organization’s data resource.
Gain a strong understanding of the legal, ethical, and societal implications of information technology with Reynolds' ETHICS IN INFORMATION TECHNOLOGY, Fifth Edition. The latest edition of this dynamic text provides up-to-date, thorough coverage of notable technology developments and their impact on business today. You will examine issues surrounding professional codes of ethics, file sharing, infringement of intellectual property, security risk assessment, Internet crime, identity theft, employee surveillance, privacy, compliance, social networking, and the ethics of IT corporations. This book offers an excellent foundation in ethical decision-making for current and future business managers and IT professionals. Unlike typical introductory Information Systems books that cover ethical issues only briefly, ETHICS IN INFORMATION TECHNOLOGY provides thorough coverage to prepare the individuals responsible for addressing ethical issues in today's workplace. You will learn how to examine ethical situations that typically arise in IT and gain practical advice for addressing the relevant issues. Up-to-the-minute business vignettes and thought-provoking questions challenge your knowledge, while features focused on decision-making--including updated Manager's Checklists--provide brief, critical points to consider in making key business decisions. Trust ETHICS IN INFORMATION TECHNOLOGY, Fifth Edition, to equip you with the understanding of IT and ethics needed for confident decision-making and professional success.
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Data Modeling Made Simple with CA ERwin Data Modeler r8 will provide the business or IT professional with a practical working knowledge of data modeling concepts and best practices, and how to apply these principles with CA ERwin Data Modeler r8. You’ll build many CA ERwin data models along the way, mastering first the fundamentals and later in the book the more advanced features of CA ERwin Data Modeler. This book combines real-world experience and best practices with down to earth advice, humor, and even cartoons to help you master the following ten objectives: 1. Understand the basics of data modeling and relational theory, and how to apply these skills using CA ERwin Data Modeler 2. Read a data model of any size and complexity with the same confidence as reading a book 3. Understand the difference between conceptual, logical, and physical models, and how to effectively build these models using CA ERwin’s Data Modelers Design Layer Architecture 4. Apply techniques to turn a logical data model into an efficient physical design and vice-versa through forward and reverse engineering, for both ‘top down’ and bottom-up design 5. Learn how to create reusable domains, naming standards, UDPs, and model templates in CA ERwin Data Modeler to reduce modeling time, improve data quality, and increase enterprise consistency 6. Share data model information with various audiences using model formatting and layout techniques, reporting, and metadata exchange 7. Use the new workspace customization features in CA ERwin Data Modeler r8 to create a workflow suited to your own individual needs 8. Leverage the new Bulk Editing features in CA ERwin Data Modeler r8 for mass metadata updates, as well as import/export with Microsoft Excel 9. Compare and merge model changes using CA ERwin Data Modelers Complete Compare features 10. Optimize the organization and layout of your data models through the use of Subject Areas, Diagrams, Display Themes, and more Section I provides an overview of data modeling: what it is, and why it is needed. The basic features of CA ERwin Data Modeler are introduced with a simple, easy-to-follow example. Section II introduces the basic building blocks of a data model, including entities, relationships, keys, and more. How-to examples using CA ERwin Data Modeler are provided for each of these building blocks, as well as ‘real world’ scenarios for context. Section III covers the creation of reusable standards, and their importance in the organization. From standard data modeling constructs such as domains to CA ERwin-specific features such as UDPs, this section covers step-by-step examples of how to create these standards in CA ERwin Data Modeling, from creation, to template building, to sharing standards with end users through reporting and queries. Section IV discusses conceptual, logical, and physical data models, and provides a comprehensive case study using CA ERwin Data Modeler to show the interrelationships between these models using CA ERwin’s Design Layer Architecture. Real world examples are provided from requirements gathering, to working with business sponsors, to the hands-on nitty-gritty details of building conceptual, logical, and physical data models with CA ERwin Data Modeler r8. From the Foreword by Tom Bilcze, President, CA Technologies Modeling Global User Community: Data Modeling Made Simple with CA ERwin Data Modeler r8 is an excellent resource for the ERwin community. The data modeling community is a diverse collection of data professionals with many perspectives of data modeling and different levels of skill and experience. Steve Hoberman and Donna Burbank guide newbie modelers through the basics of data modeling and CA ERwin r8. Through the liberal use of illustrations, the inexperienced data modeler is graphically walked through the components of data models and how to create them in CA ERwin r8. As an experienced data modeler, Steve and Donna give me a handbook for effectively using the new and enhanced features of this release to bring my art form to life. The book delves into advanced modeling topics and techniques by continuing the liberal use of illustrations. It speaks to the importance of a defined data modeling architecture with soundly modeled data to assist the enterprise in understanding of the value of data. It guides me in applying the finishing touches to my data designs.
 Data Modeling Made Simple will provide the business or IT professional with a practical working knowledge of data modeling concepts and best practices. This book is written in a conversational style that encourages you to read it from start to finish and master these ten objectives: Know when a data model is needed and which type of data model is most effective for each situation Read a data model of any size and complexity with the same confidence as reading a book Build a fully normalized relational data model, as well as an easily navigatable dimensional model Apply techniques to turn a logical data model into an efficient physical design Leverage several templates to make requirements gathering more efficient and accurate Explain all ten categories of the Data Model Scorecard Learn strategies to improve your working relationships with others Appreciate the impact unstructured data has, and will have, on our data modeling deliverables Learn basic UML concepts Put data modeling in context with XML, metadata, and agile development Book Review by Johnny Gay
In this book review, I address each section in the book and provide what I found most valuable as a data modeler. I compare, as I go, how the book's structure eases the new data modeler into the subject much like an instructor might ease a beginning swimmer into the pool.

This book begins like a Dan Brown novel. It even starts out with the protagonist, our favorite data modeler, lost on a dark road somewhere in France. In this case, what saves him isn't a cipher, but of all things, something that's very much like a data model in the form of a map! The author deems they are both way-finding tools.

The chapters in the book are divided into 5 sections. The chapters in each section end with an exercise and a list of the key points covered to reinforce what you've learned. I find myself comparing the teaching structure of the book to the way most of us learn to swim. 
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From the Hardcover edition.
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