SIGMA DHYANA
SQL for Data Analysis & Database Management
From MySQL fundamentals to window functions, indexing, performance tuning and automation with triggers.
Module 1: Introduction to SQL and MySQL Fundamentals
Objective: Understand the basics of relational databases, SQL syntax, and fundamental MySQL operations.
Overview of Relational Databases and MySQL
- Overview of Relational Databases
- Introduction to MySQL and its Features
- installing and Setting Up MySQL
- Database Clients and IDEs: MySQL Workbench
SQL Syntax and Basic Commands
- understanding SQL Syntax
- basic SQL Statements: SELECT, FROM, WHERE
- filtering and Sorting Data
- Using WHERE, ORDER BY, and LIMIT Clauses
- Implementing Advanced Filtering with AND, OR, NOT
- Real-life Example: Querying Customer Data for a Retail Business
Working with Multiple Tables
- Perform JOIN operations: INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL JOIN.
- Using aliases for table readability.
- Combining tables with UNION and UNION ALL.
- Real-life example: Combining sales and product tables for analysis.
Aggregating Data
- Use GROUP BY and HAVING clauses for data aggregation.
- Apply aggregate functions: COUNT, SUM, AVG, MIN, MAX.
- Practical examples and use cases.
- Case study: Analyzing monthly sales performance.
Subqueries and Nested Queries
- Introduction to Subqueries
- Understand subqueries and their types (correlated vs. non-correlated).
- Implement subqueries in SELECT, FROM, and WHERE clauses.
- Real-life example: Identifying top-performing products based on sales data.
Module 2: Intermediate SQL Concepts
Objective: Master data modification, database design principles, and intermediate SQL techniques.
Modifying Data
- inserting Data: INSERT INTO
- updating Data: UPDATE SET
- deleting Data: DELETE FROM
- Working with NULL Values and IS NULL
- Real-life Example: Updating Inventory Levels in a Warehouse Management System
Data Normalization and Database Design
- understanding Data Normalization
- normal Forms (1NF, 2NF, 3NF, BCNF)
- designing Efficient Database Schemas
- case Study: Normalizing a Customer Relationship Management (CRM) Database
Advanced-Data Manipulation with Window Functions
- introduction to Window Functions
- ROW_NUMBER(), RANK(), DENSE_RANK()
- aggregate Window Functions: SUM(), AVG(), MIN(), MAX()
- practical Use Cases of Window Functions
- Real-life Example: Calculating Running Totals and Moving Averages in Financial Data
Module 3: Advanced SQL Techniques
Objective: Explore advanced SQL techniques including subquery optimization, indexing, and stored procedures.
Mastering Subqueries and Correlated Subqueries
- Deep dive into subqueries and correlated subqueries.
- Optimizing subqueries for performance.
- performance Considerations and Best Practices
- Real-life example: Using complex subqueries for dynamic reporting.
Indexes and Performance Optimization
- Understanding Indexes and Their Types
- Creating and Managing Indexes
- Query Tuning and Optimization Techniques
- analyzing Query Performance with EXPLAIN
- case Study: Optimizing Queries for a High-traffic E-commerce Platform
Stored Procedures, Functions, and Triggers
- Writing stored Procedures and User-Defined Functions
- benefits and Use Cases of Stored Procedures
- Implementing triggers for Automated Tasks
- Real-life Example: Automating Inventory Updates with Triggers