Home Categories Data Modeling

Mastering Data Modeling Fundamentals

Learners: 33,500

Instructor: /

Duration:

This course is perfect for anyone looking to master the fundamentals of data modeling. Learn the techniques required to create data models for your organisation, including both the classic entity-relationship notation and the "crow's foot" notation. You will also learn how to create semantically correct data models from entities, attributes, relationships, hierarchies, and other modelling components. Finally, you will be able to use forward engineering to convert conceptual data models to logical and physical data models. Sign up now to become a data modeling expert!▼▲

Course Feature Course Overview Pros & Cons Course Provider

Go to class

Course Feature

Cost:

Paid

Provider:

Udemy

Certificate:

No Information

Language:

English

Start Date:

Course Overview

❗The content presented here is sourced directly from Udemy platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.

Updated in [July 18th, 2023]

This course, Mastering Data Modeling Fundamentals, provides learners with the techniques required to create data models for their organisation. Learners will use both the classic entity-relationship notation and the "crow's foot" notation to apply essential data modelling design ideas. They will also learn how to create semantically correct data models from entities, attributes, relationships, hierarchies, and other modelling components. Finally, learners will be introduced to forward engineering, which is used to convert conceptual data models to logical and physical data models.

Pros & Cons

Pros Cons

Clear and concise explanations: Users appreciate that the course provides a crash course in data modeling fundamentals without getting bogged down with unnecessary details. The lectures are clear and well-presented, making it easy for beginners to understand the concepts.
Practical examples and application: The course includes good examples and a real-world case study, which helps users understand how data modeling is done from conceptual to logical to physical stages. This practical approach enhances the learning experience and makes the knowledge applicable at a high level.

Lack of resources: Some users mentioned that there were no resources provided to take away from the course. They expected at least a set of summary slides or a PDF for future reference. This lack of material may hinder their ability to review the content after completing the course.
Insufficient explanations on normalization: While the course covers the basics of data modeling, some users felt that the explanations on normalization could have been better. They compared it to other materials they have reviewed on the topic and found the explanations lacking. This may leave some users wanting more in-depth understanding of normalization concepts.