Data Modeling Master Class Training Manual 4th Edition: Steve Hoberman's Best Practices Approach to Understanding and Applying Fundamentals Through Advanced Modeling Techniques

This is the fourth 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 three 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. Two 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. Explain data modeling building blocks and identify these constructs by following a question-driven approach to ensure model precision
2. Demonstrate reading a data model of any size and complexity with the same confidence as reading a book
3. Validate any data model with key "settings" (scope, abstraction, timeframe, function, and format) as well as through the Data Model Scorecard
4. Apply requirements elicitation techniques including interviewing and prototyping
5. Build relational and dimensional conceptual, logical, and physical data models through two case studies
6. Practice finding structural soundness issues and standards violations
7. Recognize situations where abstraction would be most valuable and situations where abstraction would be most dangerous
8. Use a series of templates for capturing and validating requirements, and for data profiling
9. Express how to write clear, complete, and correct definitions
10. Leverage the Grain Matrix, enterprise data model, and available industry data models for a successful enterprise architecture.

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”, he 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 recipient of the 2012 Data Administration Management Association (DAMA) International Professional Achievement Award, is the chair of the Data Modeling Zone conference, and is the author of five books on data modeling, including the bestseller Data Modeling Made Simple.