|Mastering Data Modeling||
Mastering Data Modeling
|55.90||approx. 7-9 days|
Mastering Data Modeling is a complete guide to becoming a successful data modeler. It stresses a requirements-driven approach throughout. It 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. Numerous exercises help the student master critical skills. In addition, two detailed, annotated sample conversations with users show the process in action.
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.
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.
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.