Database 1
Why?
Databases are fundamental to data science as they provide the structured foundation for storing, retrieving, and managing data. Understanding database principles is essential for working with real-world data, designing efficient data storage solutions, and ensuring data integrity. Database knowledge forms the backbone for advanced data analysis and for building robust data-driven applications.
What?
This course introduces the fundamental concepts of database systems, covering database design principles, entity-relationship modeling, relational database theory, and normalization techniques. Students will learn how to design efficient database schemas, understand the theoretical foundations of relational databases, and apply normalization rules to optimize database structures.
Curriculum:
Principles of Databases
Introduction to database concepts, advantages of database systems, database users, database environments, and the evolution of database technologies.
Database System Concept and Architecture
Overview of database architecture, client-server systems, distributed databases, and the components of database management systems (DBMS).
The Enhanced ER Model
Advanced entity-relationship modeling concepts including specialization, generalization, aggregation, and composition to represent complex data relationships.
The Relational Data Model
Fundamentals of relational databases, relations, attributes, tuples, keys, integrity constraints, and relational algebra operations.
Mapping ER Model to Relational Model
Techniques for converting entity-relationship diagrams to relational database schemas, including transformation rules for entities, relationships, and attributes.
Data Normalization
Database normalization theory, functional dependencies, normal forms (1NF, 2NF, 3NF, BCNF), and denormalization considerations for performance optimization.
Notes
Database concepts may seem abstract at first, so working through examples is key to understanding.
