Data Modeling Made Simple with CA ERwin Data Modeler r8 - Tapa blanda

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. 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 r8 to bring my art form to life.

Learn data modeling concepts and best practices, and how to apply these principles with CA ERwin Data Modeler r8. This book combines real-world experience 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 Modeler's Complete Compare features 10. Optimize the organization and layout of your data models through the use of Subject Areas, Diagrams, Display Themes, and more 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 Technologies. She is currently the senior director of product marketing at CA Technologies.About Steve Steve Hoberman is the most requested data modeling instructor in the world. Steve balances the formality and precision of data modeling with the realities of building software systems with severe time, budget, and people constraints. In his consulting and teaching, he focuses on templates, tools, and guidelines to reap the benefits of data modeling with minimal investment. He taught his first data modeling class in 1992 and has educated more than 10,000 people about data modeling and business intelligence techniques since then.Steve is the author of five books on data modeling, the founder of the Design Challenges group, and inventor of the Data Model Scorecard.®