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Data Modeling Master Class Training Manual

Bag om Data Modeling Master Class Training Manual

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 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.

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  • Sprog:
  • Engelsk
  • ISBN:
  • 9781634622110
  • Indbinding:
  • Paperback
  • Sideantal:
  • 332
  • Udgivet:
  • 14. maj 2019
  • Størrelse:
  • 215x280x18 mm.
  • Vægt:
  • 924 g.
  • 8-11 hverdage.
  • 16. januar 2025
Forlænget returret til d. 31. januar 2025
  •  

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Beskrivelse af Data Modeling Master Class Training Manual

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

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.

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