Topics

If you complete a Database Design course from beginner to high-level advanced, you should have a strong understanding of both theoretical foundations and practical skills needed to design, implement, and manage efficient, scalable, and secure databases.

Here’s a structured breakdown of the concepts you should know by the end:

🟢 Beginner-Level Concepts

1. Introduction to Databases

  • What a database is

  • Difference between DBMS and RDBMS

  • Types of databases: Relational, NoSQL, Hierarchical, Network

2. Database Models

  • Relational Model: tables, rows, columns

  • Entity-Relationship (ER) Model

  • Basic schema design

3. Basic SQL

  • SELECT, INSERT, UPDATE, DELETE

  • WHERE, ORDER BY, LIMIT, GROUP BY

  • Simple JOINs

4. ER Diagrams

  • Entities, Attributes, Relationships

  • One-to-One, One-to-Many, Many-to-Many

  • Primary keys and foreign keys

🟡 Intermediate-Level Concepts

5. Normalization

  • 1NF, 2NF, 3NF, BCNF

  • Decomposition and removing redundancy

  • Functional dependencies

6. Advanced SQL

  • Complex JOINs

  • Subqueries

  • Views, Indexes, Triggers

  • Aggregate functions

  • Stored Procedures and Functions

7. Transactions and Concurrency

  • ACID properties

  • Isolation levels

  • Locking and deadlocks

8. Schema Refinement

  • Handling anomalies

  • Refactoring bad designs

  • Schema evolution and versioning

9. Constraints

  • NOT NULL, UNIQUE, CHECK, DEFAULT

  • Foreign Key constraints and cascading

🔴 High-Level Advanced Concepts

10. Database Performance and Optimization

  • Query optimization strategies

  • Index types and usage

  • Execution plans and cost estimation

  • Partitioning and sharding

  • Caching strategies

11. Advanced Database Architectures

  • Distributed databases and CAP theorem

  • Replication (master-slave, master-master)

  • Load balancing

  • Multi-tenant design

12. Security and Access Control

  • Authentication vs Authorization

  • Roles and privileges

  • SQL injection prevention

  • Encryption at rest and in transit

13. NoSQL & Non-Relational Models

  • Key-Value Stores (Redis)

  • Document Stores (MongoDB)

  • Columnar (Cassandra)

  • Graph Databases (Neo4j)

14. Data Warehousing and OLAP

  • Star and Snowflake schemas

  • ETL processes

  • Fact and dimension tables

  • Data lakes vs data warehouses

15. Data Modeling Tools and Practices

  • Tools like ERDPlus, MySQL Workbench, dbdiagram.io

  • UML for databases

  • Reverse engineering and forward engineering

🧠 Bonus Mastery Skills (Optional but Valuable)

  • Database-as-a-Service (DBaaS): AWS RDS, Azure SQL, Firebase

  • CI/CD for Database Changes

  • Temporal Databases (time-varying data)

  • Graph Theory for Graph DB Design

  • Designing databases for event-driven and microservice architectures

Let me know if you want a printable checklist or want to align these with a real syllabus or course!

Updated on
Normalization
ACID properties