Data Modelling Masterclass 2012

Do you already know data modelling basics and want more? Take the Data Modelling Masterclass! This course starts off with an overview of the Data Model Scorecard®, ten categories for validating data model quality. Each of these categories are 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. Three case studies and many exercises reinforce the material and enable you to apply these techniques in your current projects. We will complete a full workshop where we get to practice many of the techniques learned in this course, including building subject area, logical, and physical data models.

This interactive seminar and workshop is for anyone who already knows modelling fundamentals and is seeking more advanced techniques. In this Masterclass, delegates will first apply a best practices approach to building and validating data models through the Data Model Scorecard™, a tool for validating data model quality. Delegates will then focus on a collection of intermediate and advanced modelling techniques, including advanced normalization and enterprise data modelling. The final section contains guidelines used to gain consistency across data models in areas such as in abstraction and whether to star schema or snowflake.

Delegates will learn:

• How to apply the Data Model Scorecard™

• Advanced normalization rules and limitations of the logical data model

• A value-driven approach to building the enterprise data model

• Techniques for converting the logical into an physical design

• Factors to consider in deciding whether to Star Schema or Snowflake

• Three key questions to ask yourself before you abstract

• When to use a surrogate key