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Mastering Data Modeling: A User-Driven Approachby Joseph Maguire
Synopses & Reviews
Data modeling is one of the most critical phases in the database application development process, but also the phase most likely to fail. A master data modeler must come into any organization, understand its data requirements, and skillfully model the data for applications that most effectively serve organizational needs.
Mastering Data Modeling is a complete guide to becoming a successful data modeler. Featuring a requirements-driven approach, this book clearly explains fundamental concepts, introduces a user-oriented data modeling notation, and describes a rigorous, step-by-step process for collecting, modeling, and documenting the kinds of data that users need.
Assuming no prior knowledge, Mastering Data Modeling sets forth several fundamental problems of data modeling, such as reconciling the software developer's demand for rigor with the users' equally valid need to speak their own (sometimes vague) natural language. In addition, it describes the good habits that help you respond to these fundamental problems. With these good habits in mind, the book describes the Logical Data Structure (LDS) notation and the process of controlled evolution by which you can create low-cost, user-approved data models that resist premature obsolescence. Also included is an encyclopedic analysis of all data shapes that you will encounter. Most notably, the book describes The Flow, a loosely scripted process by which you and the users gradually but continuously improve an LDS until it faithfully represents the information needs. Essential implementation and technology issues are also covered.
You will learn about such vital topics as:
"Story interludes" appear throughout the book, illustrating real-world successes of the LDS notation and controlled evolution process. Numerous exercises help you master critical skills. In addition, two detailed, annotated sample conversations with users show you the process of controlled evolution in action.
Book News Annotation:
Carlis (computer science, U. of Minnesota) and Maguire a program manager for Microsoft, explain to information systems analysts and database developers how to become a successful data modeler. Using their own Logical Data Structure for the data modeling notation, they describe in detail the process for collecting, modeling, and documenting data structures and flow. They also analyze all data shapes and provide several recipes for applying them. They provide no bibliographic references.
Annotation c. Book News, Inc., Portland, OR (booknews.com)
This book introduces Logical Data Structures (LDS), a powerful new approach to database design that can dramatically improve the cost-effectiveness and business value of any enterprise database system or database-driven application. The authors introduce a new notation, new diagramming approach, and new user-centered, high-ROI techniques for modeling even the most complex, high-volume database applications. This book starts from first principles, asking and answering crucial questions like: "To best serve users, how should the process of data modeling work? To create good, economical software systems, what kind of information should be on a data model? To become an effective data modeler, what skills should you master before talking with users?" Next, it teaches data modeling using LDS, designed to encourage a user-centered, requirements approach that leads directly to more effective applications. The authors walk you through the entire process of creating and enhancing a data model. For all database administrators, analysts, designers, and architects, and for all IT managers responsible for enterprise database system management or deployment.
You will learn about such vital topics as: *The fundamental problems of data modeling *The good habits that help a data modeler be effective and economical *LDS notation, which encourages these good habits *How to read an LDS aloud--in declarative English sentences *How to write a well-formed (syntactically correct) LDS *How to get users to name the parts of an LDS with words from their own business vocabulary *How to visualize data for an LDS *A catalog of LDS shapes that recur throughout all data models *The Flow--the template for your conversations with users *How to document an LDS for users, data modelers, and technologists *How to map an LDS to a relational schema *How LDS differs from other notations and why "Story interludes" appear throughout the book, illustrating real-world successes of the LDS notation and controlled evolution process. Numerous exercises help you master critical skills. In addition, two detailed, annotated sample conversations with users show you the process of controlled evolution in action. 020170045XB04062001
About the Author
John Carlis is on the faculty in the Department of Computer Science at the University of Minnesota. For the past twenty years he has taught, consulted, and conducted research on database systems, particularly in data modeling and database language extensions. Visit his homepage at www.cs.umn.edu/~carlis.
Joseph Maguire is an independent consultant and the creator of the forthcoming Web site www.logicaldatastructures.com. For the past 18 years he has been an employee or consultant for many companies, including Bachman Information Systems, Digital, Lotus, Microsoft, and US WEST.
Table of Contents
2. Good Habits.
3. Reading an LDS with Sentences.
4. Vocabulary of LDS.
5. Visualizing Allowed and Disallowed Instances.
6. A Conversation with Users about Creatures and Skills.
7. Introduction to Mastering Shapes.
8. One-Entity, No-Relationship Shapes.
9. One-Attribute Shapes.
10. Two-Entity Shapes.
11. Shapes with More Than Two Entities.
12. Shapes with Reflexive Relationships.
13. LDS Syntax Rules.
14. Getting the Names Right.
15. Official Name.
16. Labeling Links.
17. Documenting an LDS.
18. Script for Controlled Evolution.
19. Local, Anytime Steps of Controlled Evolution.
20. Global, Anytime Steps of Controlled Evolution.
21. Conversations about Dairy Farming.
23. LDS for LDS.
24: Decisions: Designing a Data-Modeling Notation.
25. LDS and the Relational Model.
26: Cookbook: Recipes for Data Modelers.
Appendix: Exercises for Mastery.
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