Relational data modeling is the most widely practiced of all data modeling methods, the concepts and techniques of which provide fundamental capabilities to build upon and develop more recent and more advanced modeling skills. In this course, instructor Dave Wells equips participants with the knowledge and skills to expand this practice: including logical and conceptual modeling to resolve data disparity and improving data integration efforts. He also introduces reverse engineering models from tables in SaaS, ERP, and other operational systems to capture information needed for data integration and interoperability efforts.
Purpose
To learn the techniques of entity-relationship data modeling as they are applied to conceptual, logical, and physical modeling.
Outcome
- Understand the components of entity-relationship data models: entities, relationships, and attributes
- Read an entity-relationship data model and express the meaning as simple sentences
- Develop conceptual, logical, and physical data models for relational data
- Apply normalization and abstraction techniques to logical data models
- Apply physical modeling techniques such as foreign-key mapping, data typing, and column constraints
- Reverse engineer physical and logical data models from existing relational databases
This Course Includes:
- “Check for Understanding” quizzes after each course section
- A 21-question exam
- An 88-minute educational training video
- The video is divided into smaller sections for convenient viewing
- Self-paced and on-demand e-learning
- Unlimited course access
- Downloadable exercises and resources include:
- Example Company Profile
- Example Company Key-Value Files
- Example Company Order Document Data
- Example Company Recommendations System Requirements
- Exercise Solutions
- Course slides in .pdf format
- Course CEUs: 2.0 hours
Individual Course Price: $99
Learning Plan Price: $419
Learning Plan CEUs: 10.0 hours
We offer several bulk licensing options for corporate and group use.
Contact us for a follow-up discussion!