Data Modeling Master Class Training Manual 2nd Edition: Steve Hoberman's Best Practices Approach to Understanding and Applying Fundamentals Through Advanced Modeling Techniques

The Master Class is a complete course on requirements gathering and data modeling, containing four days of practical techniques for producing solid relational and dimensional data models. After learning the styles and steps in gathering and modeling requirements, you will apply a best practices approach to building and validating data models through the Data Model Scorecard(r). You will learn not just how to build a data model, but also how to build a data model well. Challenging exercises and workshops will 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...

• Read a data model of any size and complexity
• Validate any data model with the Data Model Scorecard(r)
• Build relational and dimensional subject area, logical, and physical data models
• Use abstraction
• Gather requirements
• Leverage a series of templates for capturing requirements
• Write clear, complete, and correct definitions
• Explain the critical factors that must be in place for a successful enterprise data model
• Understand subject area, logical, and physical data models
• Ensure the model captures the requirements
• Validate model scope
• Follow acceptable modeling principles
• Determine the optimal use of generic concepts
• Apply consistent naming standards
• Arrange the model for maximum understanding
• Write clear, correct, and consistent definitions
• Match the model with the enterprise
• Compare the metadata with the data