The Master of Data Analytics in SQL program is designed to provide students with advanced knowledge and practical skills in utilizing SQL for effective data analysis. The curriculum covers a wide range of topics, including database design, querying, optimization, and data manipulation, enabling students to become proficient data analysts capable of extracting valuable insights from complex datasets.
Course Duration: 1 year (3 semesters)
Semester 1: Foundations of Data Analysis with SQL
Introduction to Data Analytics with SQL
- Understanding the role of SQL in data analysis
- Basic SQL syntax and concepts
- Setting up SQL environments
Relational Database Management Systems
- Fundamentals of relational databases
- Entity-Relationship (ER) modeling
- Normalization and denormalization
SQL Data Manipulation Language (DML)
- SELECT statements and filtering data
- Sorting and ordering result sets
- Joins and subqueries for data retrieval
Data Cleaning and Transformation
- Identifying and handling missing data
- Data quality assessment and improvement
- Using SQL for data transformation tasks
Semester 2: Advanced SQL Techniques for Data Analysis
SQL Data Definition Language (DDL)
Creating and modifying database structures
Managing tables, constraints, and indexes
Database schema design considerations
Advanced Querying and Optimization
Working with complex queries and nested subqueries
Performance optimization techniques
Using indexes and query execution plans
Window Functions and Analytical Queries
Understanding window functions and their applications
Performing ranking, aggregation, and partitioning
Time series analysis with window functions
Stored Procedures and User-Defined Functions
Creating and managing stored procedures
Developing user-defined functions in SQL
Enhancing code modularity and reusability
Semester 3: Applied Data Analytics Projects and Capstone
Database Administration and Security
User management and access control
Backup and recovery strategies
Securing sensitive data in databases
Big Data and NoSQL Integration
Introduction to NoSQL databases
Comparing SQL and NoSQL paradigms
Integrating SQL with big data technologies
Data Visualization and Reporting with SQL
Introduction to data visualization concepts
Using SQL to generate reports and dashboards
Integrating SQL results with visualization tools
Capstone Project
Applying learned concepts to a real-world data analytics project
Database design, querying, optimization, and analysis
Presenting insights and findings to peers and instructors
Note: The course syllabus is subject to change based on the institution’s curriculum guidelines and advancements in the field of data analytics and SQL technology. Additionally, hands-on labs, assignments, guest lectures, and industry case studies will be integrated throughout the program to enhance practical skills and real-world application.
