Get excited as this course provides data modelers with techniques for developing sustainable normalized and dimensional data warehouse and data mart models on relational DBMS platforms to help satisfy your business needs.
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TDWI's Data Modeling course provides data modelers with techniques for developing sustainable normalized and dimensional data warehouse and data mart models on relational DBMS platforms. The course pursues a top-down approach, which begins with a business view that depicts the major subject areas and domains of the enterprise. The models at this level are then transformed into logical models, and finally into physical models.
You Will Learn
- Differences in modeling techniques for business transactions, business events, and business metrics
- Different types of data and their implications
- Application of business context to modeling activities
- The role of business requirements in BI data modeling
- The role of source data analysis in data modeling
- Use of normalized modeling techniques for data warehouse analysis and design
- Use of dimensional modeling techniques for data warehouse analysis and design
- The roles of generalization and abstraction in data warehouse design
- The roles of identity and hierarchy management in master data management
- How time-variant data is represented in data models
- Implementation and optimization considerations for warehousing data stores
Geared To
The course is designed for practitioners familiar with traditional data modeling techniques who need to develop the data structures for business intelligence data stores. The course presumes a basic knowledge of BI architectures and traditional data modeling.
Continuing Professional Education Credits: 5
Apply these credits toward your CBIP recertification. Not certified? Learn more about CBIP and how to get certified https://tdwi.org/pages/education/cbip-certification/cbip-home.aspx here.
Instructor
Jonathan Geiger
CBIP, President
Geiger Intl, Inc.
Jonathan Geiger, CBIP, is an experienced consultant with management and hands-on experience in business intelligence, data governance, quality management, CRM, and related areas in many industries, having gained his initial experience as a program manager at an electric utility company and subsequently as a consultant. He presents frequently at national and international conferences, has written over sixty articles, and coauthored three books.