Live Online SQL Course for Data Analytics

Live Course Module: SQL Course for Data Analytics

Total Duration: 24 Hours (4 Weeks)

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Week 1: SQL Fundamentals (6 Hours)

Objective: Build foundational understanding of relational databases and SQL basics.

1. Introduction to Databases & SQL (2 hrs)

   • What is SQL and its importance in analytics

   • Database types: Relational vs Non-relational

   • SQL tools: MySQL, PostgreSQL, SQLite, MS SQL Server

   • Setting up environment and sample databases

2. Basic SQL Queries (2 hrs)

   • SELECT, FROM, WHERE, ORDER BY, LIMIT

   • Filtering and sorting data

   • Understanding NULL values and aliases

3. Data Filtering & Operators (2 hrs)

   • Logical operators (AND, OR, NOT)

   • Comparison operators and pattern matching (LIKE, IN, BETWEEN)

   • Practical exercises with sample datasets

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Week 2: Data Aggregation & Joins (6 Hours)

Objective: Learn to summarize data and combine multiple tables.

4. Aggregation & Grouping (2 hrs)

   • COUNT, SUM, AVG, MIN, MAX

   • GROUP BY and HAVING clauses

   • Aggregation for business reporting

5. Working with Joins (2 hrs)

   • INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL JOIN

   • Combining multiple tables for analysis

   • Real-world join case studies

6. Subqueries & Nested Queries (2 hrs)

   • Writing subqueries in SELECT, FROM, WHERE

   • Correlated subqueries

   • Performance tips for nested queries

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Week 3: Advanced SQL for Analytics (6 Hours)

Objective: Perform complex analytics and transformations using SQL.

7. SQL Functions & Expressions (2 hrs)

   • String, Date, and Numeric functions

   • CASE WHEN statements

   • Data formatting and cleaning

8. Window Functions & Ranking (2 hrs)

   • ROW_NUMBER, RANK, DENSE_RANK

   • Running totals, moving averages

   • Analytical insights using window functions

9. CTEs and Temporary Tables (2 hrs)

   • Common Table Expressions (WITH clause)

   • Temporary and derived tables

   • Building complex queries step-by-step

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Week 4: Data Analytics Applications & Projects (6 Hours)

Objective: Apply SQL in real-world analytics and visualization workflows.

10. Data Manipulation & Transformation (2 hrs)

• INSERT, UPDATE, DELETE

• Data validation and cleaning techniques

• Combining SQL with Excel/Python for analysis

11. SQL for Business & Analytics (2 hrs)

• Exploratory data analysis using SQL

• Customer segmentation, trend analysis, and KPI tracking

• Real business use cases

12. Capstone Project & Assessment (2 hrs)

• Live project using real dataset

• Build queries to generate business insights

• Instructor evaluation and feedback

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🎯 Learning Outcomes

By the end of this course, learners will be able to:
✅ Write efficient SQL queries for real-world data analysis
✅ Perform aggregations, joins, and subqueries on large datasets
✅ Use window functions and CTEs for advanced analytics
✅ Clean, manipulate, and transform data using SQL
✅ Apply SQL to business intelligence and dashboard workflows

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