SQL for Data Analytics

45-Day Schedule

Week 1: Introduction to SQL Basics

Learn the basics of SQL, setup tools, and perform basic queries.

Week 2: Aggregations and Grouping

Master aggregate functions and grouping data for deeper insights.

Week 3: Joins and Subqueries

Learn how to combine multiple tables using joins and subqueries.

Week 4: Data Manipulation

Learn how to insert, update, delete, and manipulate data.

Week 5: Advanced SQL for Data Analytics

Explore window functions, recursive queries, and indexing for optimization.

Week 6: Real-World Data Analytics and Final Project

Apply SQL techniques in real-world scenarios and complete a final project.

Course Information

Prerequisites: Basic programming knowledge is recommended.

Skills Covered: SQL, Data Aggregation, Joins, Subqueries, Data Manipulation, Advanced SQL Techniques, Business Analytics.

Course Outcomes: Build data analytics skills with hands-on projects, including a final project to integrate all learning.

Modules

Introduction to SQL Basics

Learn the basics of SQL syntax, setup tools, and perform queries.

Understanding Databases
Basic SQL Syntax
Using SELECT, FROM, WHERE

Aggregations and Grouping

Master aggregate functions and grouping data.

COUNT, SUM, AVG, MIN, MAX
GROUP BY, HAVING
Working with Dates and Time in SQL

Joins and Subqueries

Learn to combine data from multiple tables with joins and subqueries.

INNER JOIN, LEFT JOIN, RIGHT JOIN
Correlated and Non-Correlated Subqueries
Using Subqueries in SELECT, FROM, and WHERE

Data Manipulation

Manipulate data with INSERT, UPDATE, DELETE commands.

Inserting Data into Tables
Updating Data with Conditions
Deleting Data with WHERE Clause

Final Project

Project Description: Build an end-to-end data analytics pipeline using SQL, including:

Data Cleaning and Preprocessing
Exploratory Data Analysis (EDA)
SQL-based Data Analysis and Reporting
Visualizations and Insights

Deployment: Deploy the solution using a BI tool like Tableau or Power BI for real-world business analytics.