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Data Modeling Master Class Training Manual 8Th Edition: Steve Hoberman'S Best Practices Approach To Understanding And Applying Fundamentals Through Advanced Modeling Techniques

Data Modeling Master Class Training Manual 8Th Edition: Steve Hoberman'S Best Practices Approach To Understanding And Applying Fundamentals Through Advanced Modeling Techniques

Data Modeling Master Class Training Manual 8Th Edition: Steve Hoberman'S
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Data Modeling Master Class Training Manual 8Th Edition: Steve Hoberman'S Best Practices Approach To Understanding And Applying Fundamentals Through Advanced Modeling Techniques Paperback - 2019

by Steve Hoberman

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  • Title Data Modeling Master Class Training Manual 8Th Edition: Steve Hoberman'S Best Practices Approach To Understanding And Applying Fundamentals Through Advanced Modeling Techniques
  • Author Steve Hoberman
  • Binding Paperback
  • Condition New
  • Pages 332
  • Volumes 1
  • Language ENG
  • Publisher Technics Publications
  • Publication date 2019-05-14
  • Bookseller's Inventory # 35808335
  • ISBN 9781634622110 / 1634622111
  • Weight 1.7 lbs (0.77 kg)
  • Dimensions 11 x 8.5 x 0.69 in (27.94 x 21.59 x 1.75 cm)
  • Category Computers - Data Base Management
  • Quantity available 5

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From the publisher

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(R). 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

  1. Determine how and when to use each data modeling component
  2. Apply techniques to elicit data requirements as a prerequisite to building a data model
  3. Build relational and dimensional conceptual, logical, and physical data models
  4. Incorporate supportability and extensibility features into the data model
  5. Assess the quality of a data model.

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