Master the foundational concepts of databases, from data organization and SQL queries to advanced topics like normalization and transaction management.
Understanding Data vs Information, Database definitions, and why we need DBMS over File Systems.
Three Schema Architecture, Data Independence, Schemas & Instances, and Database Languages.
Entity, Attributes, Relationships, Strong vs Weak Entities, and ER Diagram Symbols.
Keys, Constraints, and the foundational structure of RDBMS tables, tuples, and relationships.
Complete guide to SQL: Core Concepts, Terminologies, and Commands (DQL, DDL, DML, etc.).
Functional Dependencies, Anomalies, and Normal Forms (1NF, 2NF, 3NF, BCNF) to reduce data redundancy.
Understand transactions, the critical ACID properties (Atomicity, Consistency, Isolation, Durability), and the lifecycle states of a transaction.
Implementation level details of how DBMS ensures Atomicity and Durability using Shadow-copy and Log-based recovery methods.
Learn how indexing optimizes performance through Primary, Secondary, and Multi-level indexing techniques.
Explore non-relational database models, flexible schemas, horizontal scaling mechanisms (Sharding & Replica-sets), and failover architectures.
Explore the four major models: Relational, Object-Oriented, NoSQL, and Hierarchical databases with their respective traits and trade-offs.
Master database clustering, load balancing mechanisms, active replication models, and failover operations for high availability.
Explore vertical and horizontal partitioning, database scaling limits, and distributed architectures like Sharding to support ultra-large datasets.
Understand database design patterns and scaling strategies through a step-by-step case study of a real-world cab booking application.
Explore Consistency, Availability, and Partition Tolerance, the trade-off formalization, and RDBMS split-brain behaviors.
Understand read-write segregation, asynchronous log synchronization, replication lag trade-offs, and clustering integrations.