Advanced SQL + DBMS
Query Optimization, Indexing, Triggers, Enterprise Design & NoSQL
An intensive 2.5-month advanced curriculum engineered for developers and data professionals looking to master high-performance database engineering.
Conquer complex analytical queries with window functions, Common Table Expressions (CTEs), and recursive queries.
Master database indexing strategies, query execution plans (EXPLAIN ANALYZE), performance tuning, and stored logic with procedures and triggers.
Design enterprise-scale relational schemas, explore modern NoSQL document stores with MongoDB, and deliver a production-ready capstone database project.
Program Details
Program Roadmap
Advanced Query Techniques
Write complex analytical queries using window functions, CTEs, and recursive hierarchy traversal.
- ●Window Functions Architecture: Partitioning and Ordering Windows
- ●Ranking Functions: Row Number, Rank, Dense Rank, and Quantiles
- ●Lead, Lag, First Value, and Running Aggregate Calculations
- ●Modular Common Table Expressions (CTEs) for Readability
- ●Recursive Queries for Hierarchical Trees and Organizational Graphs
Indexing & Optimization
Analyze query execution plans, design optimal indexes, and eliminate query bottlenecks.
- ●Internal Database Storage: Pages, Blocks, and Buffer Pools
- ●B-Tree Indexes, Clustered vs Non-Clustered Indexes, and Composite Keys
- ●Deciphering Query Execution Plans and Query Cost Estimations
- ●Diagnosing Full Table Scans and Eliminating Slow Join Strategies
- ●Covering Indexes, Index SARGability, and Optimizer Statistics
Stored Procedures & Triggers
Automate database business logic, enforce integrity rules, and handle complex transactions.
- ●Stored Procedures and User-Defined Functions for Encapsulated Logic
- ●Control Flow, Conditional Branches, and Error Handlers in SQL
- ●Event-Driven Triggers for Audit Trails and Automated Data Synchronization
- ●ACID Transactions, Savepoints, and Rollback Protocols
- ●Locking Mechanisms, Transaction Isolation Levels, and Deadlock Prevention
Database Design
Design production-grade, highly scalable schemas with advanced normalization and modeling.
- ●Higher Normal Forms: Boyce-Codd Normal Form (BCNF) and Fourth Normal Form
- ●Strategic Denormalization Patterns for High-Throughput Read Scalability
- ●Enterprise Entity-Relationship Modeling with Complex Cardinalities
- ●Horizontal Table Partitioning: Range, List, and Hash Strategies
- ●Read Replicas, Sharding Architecture, and High Availability Concepts
NoSQL Overview
Compare relational vs non-relational databases and learn document stores with MongoDB.
- ●Relational vs NoSQL Paradigms: The CAP Theorem and ACID vs BASE
- ●Document Databases with MongoDB: Collections and BSON Documents
- ●Flexible Schema Modeling, Document Nesting, and Referencing
- ●MongoDB Aggregation Pipeline for Multi-Stage Analytical Processing
- ●Architectural Decision Matrix: Choosing the Right Database for the Job
Capstone Project
Design, optimize, and query a real-world enterprise database end-to-end.
- ●Enterprise System Architecture and Scalable Schema Blueprint
- ●Production DDL Implementation with Stored Procedures and Triggers
- ●Large-Scale Data Seeding and Stress-Testing Queries Under Load
- ●Query Performance Tuning with Strategic Indexing and Benchmarking
- ●Comprehensive Architectural Documentation and Portfolio Presentation
From Learning to Production
What You'll Gain
Advanced query mastery
window functions (ROW_NUMBER, RANK, DENSE_RANK, LAG/LEAD), CTEs, and recursive hierarchy queries
Query performance tuning
B-tree indexes, execution plans (EXPLAIN), and query cost reduction
Database automation
robust stored procedures, functions, triggers, and ACID transaction locks
Enterprise database architecture
advanced normalization (BCNF, 4NF), partitioning, and ER modeling
NoSQL & polyglot persistence
MongoDB document storage, indexing, and relational vs non-relational trade-offs
Production-style capstone project
build, tune, and query an enterprise-scale database for your portfolio