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After introducing the basic concepts and principles, the course addresses data modeling techniques and practices in four modeling areas: conceptual, logical, physical and dimensional. The course first addresses the collection of user requirements, followed by design approaches for logical and physical models. You will study real-world examples of data models for transactional systems, data marts and enterprise data warehouses. Expert instructors will share their practical experiences.
This is a hands-on course using an industry-leading data modeling tool in class. By the end of the course, you will be able to create data models for enterprise applications.
At the conclusion of the course, you should be able to
- Describe the various types and advantages of Data Modeling
- Discuss the quantifiable values of Data Modeling
- Explain the intricacies of Data Modeling
- Identify the use cases for Data Modeling
- Overview of data modeling
- Principles of data modeling
- Types of data modeling: Conceptual, Logical, and Physical
- Logical data modeling: Building data models; Cardinality rules; Transformation rules
- Physical data modeling: Database standards; Domains and classwords; Roll-ups and roll-downs; Data model repository options
- Dimensional data modeling: Star schema modeling; Snow flake modeling
- Top ten mistakes to be avoided
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Estimated Cost: $740
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