Advanced Course

Database Design & Data Modeling

Learn to design robust database schemas through conceptual, logical, and physical modeling. Master ER diagrams, understand design trade-offs, and make informed architectural decisions.

6-8 weeks Intermediate Level 10 modules
Database architecture and design diagrams

What You'll Learn

Database design is about making conscious decisions with full understanding of trade-offs. This course teaches you to evaluate requirements, model relationships, and create schemas that serve both current needs and future evolution.

Modeling Skills
  • Conceptual data modeling
  • Logical model design
  • Physical implementation
  • ER diagram creation
  • Entity and relationship analysis
Design Principles
  • Normalization depth decisions
  • Denormalization strategies
  • Schema evolution patterns
  • Performance vs integrity trade-offs
  • Real-world design patterns

Design Philosophy

Good database design is not about following rules blindly. It's about understanding principles deeply enough to know when and why to apply them. Every design decision has consequences that compound over time.

This course teaches you to think through requirements systematically, identify entities and relationships with precision, and evaluate design alternatives based on concrete trade-offs. You'll learn patterns that work and anti-patterns that fail, always with the reasoning explained.

Prerequisites

This course assumes familiarity with SQL and basic database concepts. We recommend completing our SQL Fundamentals course first, or having equivalent practical experience with relational databases.

Course Details

Prerequisites

SQL knowledge required. Understanding of tables, relationships, and basic queries.

Time Commitment

6-8 hours per week for 6-8 weeks. Self-paced learning.

What's Included
  • Design methodology lessons
  • Real schema examples
  • Modeling exercises
  • Design review templates
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Course Curriculum

Module 1: Design Foundations

  • What database design means
  • Three levels of modeling: conceptual, logical, physical
  • Requirements gathering and analysis
  • Identifying entities and attributes

Module 2: Entity-Relationship Modeling

  • ER diagram notation and conventions
  • Cardinality and participation constraints
  • Weak entities and identifying relationships
  • Associative entities for many-to-many relationships

Module 3: Normalization In-Depth

  • Functional dependencies explained
  • Normal forms: 1NF through BCNF
  • Recognizing normalization opportunities
  • When normalization helps and when it hurts

Module 4: Relationship Patterns

  • One-to-one relationships and their uses
  • One-to-many: the most common pattern
  • Many-to-many through junction tables
  • Self-referencing relationships (hierarchies, networks)

Module 5: Schema Design Patterns

  • User account and authentication schemas
  • Product catalog designs
  • Order and transaction structures
  • Content management patterns
  • Time-series and event data

Module 6: Denormalization and Trade-offs

  • Why denormalization exists
  • Read vs write optimization
  • Calculated fields and aggregates
  • Caching strategies at the database level

Module 7: Constraints and Integrity

  • Domain constraints and data types
  • Entity integrity through primary keys
  • Referential integrity with foreign keys
  • Check constraints and business rules

Module 8: Schema Evolution

  • Planning for change
  • Migration strategies
  • Backward compatibility considerations
  • Versioning approaches

Module 9: Performance Considerations

  • Index design and placement
  • Query patterns influencing structure
  • Partitioning and sharding concepts
  • When to optimize and when to wait

Module 10: Design Case Studies

  • Analyzing existing schema designs
  • Common design mistakes and fixes
  • Complete design walk-through projects
  • Design review and critique practice
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