Grokking Relational Database Design and Modeling

What the course covers

The course, listed as Relational Database Design and Modeling for Software Engineers, has eight chapters (as shown on the course page in September 2026):

1. Introduction: course overview, how data was managed before databases, and key terms.
2. Fundamental concepts: what a database and a DBMS are, relational databases, and relational versus non relational systems.
3. Data modelling: the levels of data modelling (conceptual, logical, physical), the modelling process and best practices.
4. Entity relationship modelling: entities, attributes and relationships, cardinality and participation, relationship attributes, weak entities, and a worked ER diagram for an employee management system.
5. The relational model: relations, tuples and attributes, keys, integrity constraints, and converting ER diagrams into tables.
6. Functional dependency: types of dependency, inference rules and attribute closure, the theory behind normalisation.
7. Normalisation: first, second and third normal form, Boyce-Codd normal form and higher normal forms, with two worked exercises and runnable SQL exercises.
8. Case studies: hospital management, hotel management, a bank, an Instagram style app, an e-commerce platform, online food delivery, a library, ticket booking and a warehouse inventory system, followed by a final exam.

Numbers at a glance

From the course page in September 2026: 62 lessons, about 5 hours of material, beginner level, and a 4.4 out of 5 rating from 1,596 ratings. There are 113 assessments in total, including chapter quizzes, flashcard decks for vocabulary heavy chapters, written exercises with worked solutions and a final exam. A certificate of completion is issued and can be shared on LinkedIn. The course page listed a one time payment of $98 with lifetime access at that time; check the page for the current price and bundles.

Why the data model matters most

Application code gets rewritten and frameworks get replaced, but a schema with production data in it is close to permanent. Awkward queries, duplicated data and painful migrations years later usually trace back to a modelling decision made in the first week. Learning to model well is one of the highest leverage skills a backend developer can build, and it is also the foundation of many system design and database course questions.

Who it suits

• Computer science students taking a databases course who want the theory (functional dependencies, normal forms) explained clearly with examples.
• Self taught and bootcamp developers who learned SQL through an ORM and never studied design.
• Backend developers who have inherited a schema they cannot explain and want the vocabulary to improve it.
• Anyone preparing for technical assessments that include ER diagrams or normalisation questions.

No prior database theory is needed. Basic familiarity with tables and simple SQL helps.

How to get the most out of it

• Draw every diagram yourself. Before reading each case study, sketch your own ER diagram and table design, then compare.
• Do the runnable SQL exercises in the normalisation chapter rather than just reading the solutions.
• Model something real. Take a system you know, such as a university portal or your final year project, and design its schema using the course's process.
• Write the queries. After designing a schema, write the five queries the product actually needs. Schemas look fine until you query them.
• Use the flashcards for revision before exams or assessments.

What you will be able to do afterwards

You should be able to turn requirements into an ER diagram, convert it into well structured tables with correct keys and constraints, normalise to 3NF or BCNF and recognise when to stop, and explain your choices clearly.

Pair it with: the modern API design course in this library, since good APIs sit on top of a sound data model.

Best for: students and developers who want a clear, practical foundation in relational schema design.