Data Modelling Masterclass 2013

The Masterclass starts off with an overview of the Data Model Scorecard®, ten categories for validating data model quality. Each of these categories is then discussed, with an emphasis on advanced techniques and guidelines within data modelling and requirements elicitation. You will know not just how to build a data model, but also how to build a data model well. Several case studies and many exercises reinforce the material and enable you to apply these techniques in your current projects.

Learning Objectives

Validate any data model through the Data Model Scorecard®
Apply requirements elicitation techniques including interviewing and prototyping
Practice finding structural soundness issues and standards violations
Recognize situations where abstraction would be most valuable and situations where abstraction would be most dangerous
Use a series of templates for capturing and validating requirements, and for data profiling
Express how to write clear, complete, and correct definitions
Leverage the Grain Matrix, enterprise data model, and available industry data models for a successful enterprise architecture.