Prerequisite: This course assumes basic knowledge of data modeling concepts.
One- or Two-Day Course
How can you develop an enterprise data model or a logical data model for your BI, MDM, data governance, or data integration effort in a fraction of the time while increasing its quality? This course provides a method, as well as a toolkit of patterns, common universal data models, and industry data models. It will cover template or “universal” data models for the most common types of applications, such as modeling information about people, organizations, customers, demographics, contact information, products, services, and many standard models. You will learn how to apply these models to various types of industries, including examples of industry universal data models such as for telecommunications, manufacturing, healthcare, insurance and financial services. You’ll explore best practice ways to model roles, classifications, hierarchies, statuses, and rules. You will also learn the variations in modeling these types of constructs and share the pros and cons of each alternative.
These patterns have been through extensive iterations for over a decade and have been widely used by organizations around the world to jump-start and/or quality-assure all types of data modeling efforts. These patterns provide specific, business-oriented, and easy-to-understand ways to model these constructs, as well as generalized and flexible ways to model the same types of common information requirements. These models, hints, and techniques could save your organization hundreds or thousands of hours by avoiding unnecessary modeling, redesigns, or mistakes, and by developing consistent models.
You Will Learn
- Universal data models for common functions as well as industry-specific models
- Powerful patterns for modeling common types of data such as roles, statuses, categories, hierarchies, and rules, using specific and generalized styles of modeling
- How to use this toolkit of universal data model patterns in different scenarios and for different audiences, from business representatives to DBAs
- Pros and cons of specific versus generalized ways to model and when to use different styles
- Pitfalls in data modeling and “war stories” illustrating consequences of incorrect modeling; examples and experiences of how organizations have applied these models and patterns
- How to apply these models and patterns through hands-on exercises
Geared To
- Data modelers, data warehouse designers, data analysts, data administrators, database designers, database administrators, database consultants, and any other information systems professionals who need to be involved in data warehouse designs, data models, database designs, and data integration issues