Data Modeling Master Class Training Manual 3rd Edition: Steve Hoberman's Best Practices Approach to Understanding and Applying Fundamentals Through Advanced Modeling Techniques - Softcover

Hoberman, Steve

Softcover

ISBN 10: 1935504169 ISBN 13: 9781935504160

Publisher: Technics Publications, LLC, 2011

Synopsis

This is the third edition of the training manual for the Data Modeling Master Class that Steve Hoberman teaches onsite and through public classes. This text can be purchased prior to attending the Master Class, the latest course schedule and detailed description can be found on Steve Hoberman's website, stevehoberman.com.

The Master Class is a complete course on requirements elicitation and data modeling, containing four days of practical techniques for producing solid relational and dimensional data models. After learning the styles and steps in capturing and modeling requirements, you will apply a best practices approach to building and validating data models through the Data Model Scorecard®. You will know not just how to build a data model, but also how to build a data model well. Three case studies and many exercises reinforce the material and enable you to apply these techniques in your current projects.

By the end of the course, you will know how to:

1. Apply requirements elicitation techniques including interviewing and prototyping
2. Explain data modeling constructs and employ the "6 Questions" approach to ensure model precision
3. Demonstrate reading a data model of any size and complexity with the same confidence as reading a book
4. Validate any data model with key "settings" (scope, abstraction, timeframe, function, and format) as well as through the Data Model Scorecard®
5. Practice finding structural soundness issues and standards violations
6. Build relational and dimensional subject area, logical, and physical data models
7. Recognize situations where abstraction would be most valuable and situations where abstraction would be most dangerous
8. Use a series of templates for scoping and validating requirements, and for data profiling
9. Express how to write clear, complete, and correct definitions
10. Describe the two reasons an enterprise data modeling project can fail, and the factors that must be in place for the enterprise data model to succeed

About this title

About the Author

Steve Hoberman is the most requested data modeling instructor in the world. Introduced at over 50 international conferences as everything from a data modeling guru to data modeling rock star , 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, spanning every continent except Africa and Antarctica. Steve is known for his entertaining, interactive teaching and lecture style (watch out for flying candy!), and organizations around the globe have brought Steve in to teach his Data Modeling Master Class, which is recognized as the most comprehensive data modeling course in the industry. Steve is the author of five books on data modeling, including the bestseller Data Modeling Made Simple. He is the founder of the Design Challenges group, inventor of the Data Model Scorecard®, and CEO of Technics Publications.

From the Inside Flap

The Master Class is a complete course on requirements elicitation and data modeling, containing four days of practical techniques for producing solid relational and dimensional data models. After learning the styles and steps in capturing and modeling requirements, you will apply a best practices approach to building and validating data models through the Data Model Scorecard.® You will know not just how to build a data model, but also how to build a data model well. Three case studies and many exercises reinforce the material and enable you to apply these techniques in your current projects.Top 10 Objectives 1. Apply requirements elicitation techniques including interviewing and prototyping 2. Explain data modeling constructs and employ the 6 Questions approach to ensure model precision 3. Demonstrate reading a data model of any size and complexity with the same confidence as reading a book 4. Validate any data model with key settings (scope, abstraction, timeframe, function, and format) as well as through the Data Model Scorecard® 5. Practice finding structural soundness issues and standards violations 6. Build relational and dimensional subject area, logical, and physical data models 7. Recognize situations where abstraction would be most valuable and situations where abstraction would be most dangerous 8. Use a series of templates for scoping and validating requirements, and for data profiling 9. Express how to write clear, complete, and correct definitions 10. Describe the two reasons an enterprise data modeling project can fail, and the factors that must be in place for the enterprise data model to succeed Steve Hoberman is the most requested data modeling instructor in the world. Introduced at over 50 international conferences as everything from a data modeling guru to data modeling rock star , 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, spanning every continent except Africa and Antarctica. Steve is the author of five books on data modeling, including the bestseller Data Modeling Made Simple.

Edition details

• Publisher: Technics Publications, LLC
• Publication date: 2011
• Language: English
• ISBN 10: 1935504169
• ISBN 13: 9781935504160
• Binding: Paperback
• Edition number: 3
• Number of pages: 462