Data Modeling Master Class Training Manual
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Language: English
Published by Technics Publications LLC (US), 2019
- Softcover
- New

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Seller Inventory # 9781634622110
- Title
- Data Modeling Master Class Training Manual
- Author
- Steve Hoberman
- Publisher
- Technics Publications LLC (US)
- Publication year
- 2019
- Condition
- New
- Binding
- Paperback
- Language
- English
- ISBN 10
- 1634622111
- ISBN 13
- 9781634622110
This is the eighth 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 data modeling course, containing three days of practical techniques for producing conceptual, logical, and physical relational and dimensional and NoSQL 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 how to build a data model well. Three case studies and many exercises reinforce the material and will enable you to apply these techniques in your current projects.
Top 5 Objectives:
The Master Class is a complete data modeling course, containing three days of practical techniques for producing conceptual, logical, and physical relational and dimensional and NoSQL 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 how to build a data model well. Three case studies and many exercises reinforce the material and will enable you to apply these techniques in your current projects.
Top 5 Objectives:
- Determine how and when to use each data modeling component
- Apply techniques to elicit data requirements as a prerequisite to building a data model
- Build relational and dimensional conceptual, logical, and physical data models
- Incorporate supportability and extensibility features into the data model
- Assess the quality of a data model
"Synopsis" may belong to another edition of this title.
About the Author
Steve Hoberman 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 over ten 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®, Conference Chair of the Data Modeling Zone conference, recipient of the 2012 Data Administration Management Association (DAMA) International Professional Achievement Award, and highest rated workshop presenter at Enterprise Data World 2014 and 2015. Steve can be reached at me@stevehoberman.com, @DataMdlRockStar on Twitter, or through Steve Hoberman on Linked-In.
"About the title" may belong to another edition of this title.
Gazelle Books
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