Data Modeling Scheme

Explain the strengths of each and the differences among the 12 types of data models. Create business terms, logical, and physical data models across relational, dimensional, document, and graph approaches. Apply practical techniques such as normalization, dimensional grain and meter design, JSON nested arrays, graph patterns (RDF and Property), denormalization, indexing, views, and partitioning. This course gives learners a complete journey through the Align (common business vocabulary), Refine (business requirements), and Design (technical solution) approach. Much more than a lecture, you will see lots of examples, compare modeling approaches, and build models step by step. By the end of the course, you will be better prepared to choose the right type of model for the right need and communicate your decisions with confidence. What makes this course unique is its breadth and practicality. Most courses stay in one modeling world. This one brings together relational, dimensional, document, and graph in one clear framework. It also connects business vocabulary, business requirements, and technical design through the powerful Align/Refine/Design approach, so learners can see how modeling works from start to finish. This is a course for people who want to become more competent and versatile data modelers.