Course Overview
About Course
The 40-hour Database Training program equips practitioners with both foundational and advanced skills in modern data management. Kicking off with database fundamentals, it lays groundwork in architecture, relational vs NoSQL systems, data models, ER modeling, and normalization—covering crucial relational theory and schema design practices .
Participants learn to craft robust SQL queries through modules on CRUD operations, filtering, joins, transactions, and advanced constructs like stored procedures, functions, indices, and triggers. A standout feature is performance tuning, indexing strategies, transaction handling, isolation levels, and rollback management—key concepts for enterprise-grade data systems .
Module 4 delves into design best practices—transitioning ERDs into normalized relational schemas with a focus on functional dependencies. This is followed by exploration of non-relational databases (document, key-value, wide-column, spatial, functional, and graph systems), helping developers choose the right model for varying data demands .
Hands-on exposure to tools like MySQL Workbench and Database Workbench enables students to model, query, and manage databases via visual interfaces, reverse-engineering, and schema synchronization . ORM frameworks (Hibernate, SQLAlchemy) are also covered to bridge relational data with modern app layers
Emphasizing enterprise readiness, the training includes modules on backup, recovery, high availability, clustering, and robust database security measures like encryption and role-based access. Cloud database systems such as AWS RDS, Google Cloud SQL, Spanner, and Bigtable are introduced through migration labs and real-world usage scenarios
The capstone integrates these learnings into a functional, multi-database solution with performance optimization, high availability configuration, and backup strategies. Participants emerge with a strong portfolio project, mastery of varied database systems, and readiness for roles in database administration, data engineering, or architecture within modern, data-driven enterprises.
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Course Syllabus
Module 1: Introduction to Databases (4 hrs)
- Core concepts: data, DBMS vs files
- DB types: relational, NoSQL, spatial, object-oriented
- ER models, relational model, normalization essentials
Module 2: SQL & CRUD Operations (6 hrs)
- Data definition & manipulation: CREATE, INSERT, SELECT, UPDATE, DELETE
- Filtering, sorting, expressions, joins, aggregations; labs for set operations
Module 3: Advanced SQL & Database Structures (6 hrs)
- Views, indexes, stored procedures, triggers, functions
- Transactions, ACID, isolation levels, rollbacks
- Query optimization and performance tuning
Module 4: Relational DB Design & Normalization (5 hrs)
- ER-to-relational mapping, schema design, advanced normalization
- Functional dependencies and schema refinement
Module 5: NoSQL & Specialized Databases (5 hrs)
- Introduction to NoSQL types: document, key‑value, wide‑column, graph
- Overview of spatial, time-series, and functional databases
- When to use each type
Module 6: SQL Tools & GUI (4 hrs)
- Tool demos: MySQL Workbench, Database Workbench
- ER diagrams, schema management, reverse-engineering
Module 7: ORM & Application Integration (4 hrs)
- ORM concepts: object-relational mapping with Hibernate, SQLAlchemy
- Integration in typical backend stacks
Module 8: Backup, Security & High Availability (5 hrs)
- Backup/restore strategies, replication, clustering, HA principles
- Security: access control, encryption, auditing, roles
Module 9: Cloud Databases & Big Data (4 hrs)
- Cloud-managed DBs: AWS RDS, Cloud SQL, Spanner, Bigtable
- Use-case labs: schema design, migrations
Module 10: Capstone Project & Review (2 hrs)
- Build integrated schema with hybrid SQL/NoSQL setup
- Optimize queries, implement backups and HA
- Final presentation and peer code review
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Key Features
- Hands-on labs: Each module includes real-data exercises (CRUD, normalization, SQL tuning).
- Tool exposure: Proficiency in tools like MySQL Workbench, Database Workbench for schema design & management
- Deep dives: Advanced topics—transactions, stored procedures, triggers, indexing, ACID compliance.
- Diverse DB exposure: Learn relational and non-relational systems, spatial, functional, and graph models .
- Cloud and Big Data: Work with managed DB services (Cloud SQL, Bigtable, Spanner) and migration scenarios
- Security & availability: Focused training on backup, HA, clustering, encryption, access control.
- ORM & integration: Bridge between databases and application layers using popular ORMs.
- Capstone project: Build and optimize a real-world multi-DB solution with performance tuning, HA, backups, and report deliverables.



