SQL for Data Analytics

Name: SQL for Data Analytics
Rating: 4.2 (16 reviews)

MySQL, Relational database, Structured Query Language

Created byAravindan Madhavan, Ramya T, Dr. Nithya V

Last updated 7/2025

English

English [Auto],

What you'll learn

Understand and execute SQL query
Understand Database Structures and entity relationships
Clean and transform data effectively
Retrieve and manipulate data using SQL queries

Course content

5 sections • 21 lectures • 5h 15m total length

Introduction to Database Management Systems15:44
Explore data concepts, database management systems, and relational databases, including primary and foreign keys, and learn SQL using MySQL and MySQL Workbench.
Installing MySQL17:38
Install MySQL using the Windows installer for version 8.0.41, select components including server and workbench, configure with a strong root password, and verify the connection.
Exploring MySQL Workbench9:43
Explore MySQL Workbench interface to create and run SQL in testdb, import data, monitor server status, and manage schemas, tables, stored procedures, and functions.
Relationship Diagram6:26
Explore the enhanced entity-relationship diagram (EER) concepts, including subclasses, union types, constraints, and strong versus weak relationships, and learn to reverse engineer a database with MySQL Workbench.
SQL Datatypes and Constraints13:03
Learn about SQL data types—numeric, character, date/time, and binary—and constraints such as primary key, foreign key, not null, unique, check, and default, with table creation.

Data Definition Language (DDL)19:32
Master data definition language (DDL) in SQL for data analytics. Learn create, alter, truncate, drop, and rename commands and how they define or modify databases and tables.
Understanding SQL Statements: DML15:23
Learn data manipulation language (DML) in SQL by using insert, select, update, and delete to manage data, and situate these within DDL, DCL, and TCL.
Understanding SQL Statements: DCL21:49
Understand data control language (DCL) in SQL, including grant, revoke, show grants, and flush privileges, to manage user access and privileges on databases and tables.
Understanding SQL Statements:TCL11:00
Learn how transaction control language (tcl) manages dml changes as a single logical unit, using begin, commit, rollback, savepoint, and set transaction for permanent saves and partial rollbacks.
Pattern Matching13:14
Explore pattern matching in SQL by using the like operator with wildcards, percentage and underscore, to search data when exact values are unknown, with examples from the Awesome Chocolates database.

Aggregate Functions (Calculation in Queries)14:01
Master SQL aggregate functions like min, max, sum, average, and count to perform calculations on numeric columns, group results with group by, and order by for insightful analytics.
Group By and Order By Clause15:47
Explore group by and order by in sql to sort sales by amount, aggregate totals per salesperson with sum, and filter by geography id and product id with limit.
Condition in Queries : Where Clause, Having Clause, Case Statement27:27
Learn to write SQL conditions using where, having, and case statements, with operators and pattern matching like, between, and in; understand group by with having for aggregates.
SQL Window Functions6:23
Master sql window functions to compute running totals and rankings within partitions using over, partition by, and order by, with aggregate and ranking functions like sum, row_number, rank, and dense_rank.
SQL_Window Function_Demo12:32
Explore SQL window functions for data analytics, applying max over partitions, row_number, rank and dense_rank, and using lag, lead, first_value and last_value to compute aggregates without altering data.

Joins : Part 1 - Inner Join, Left Join, Right Join24:53
Learn to combine data with SQL joins, focusing on inner join, left join, and right join, with overviews of full, cross, and self-joins and practical MySQL examples.
Joins: Part 2 - Full Join, Cross Join, Self Join13:33
Explore full join, cross join, and self join concepts in SQL, including how to simulate full join with unions in MySQL, and how to use self joins for hierarchical data.
Common Table Expression (CTE)27:14
Learn how common table expressions (ctes) simplify complex sql queries by breaking them into blocks using the with clause, optional column names, and unions or joins.
View : Create, Delete, Modify10:52
View is a virtual table derived from an sql statement that joins multiple tables to present data as one, and this lecture covers creation, replacement, dropping, advantages, and disadvantages.

Stored Procedures12:50
Learn how stored procedures bundle SQL statements into reusable, efficient routines that improve security; create with begin and end blocks, change delimiters, and call or drop them.
Stored procedure using while, repeat6:51
Learn to create SQL stored procedures with if else, case statements, and loops (while and loop), declare variables, and call procedures returning Tamil Nadu, Maharashtra, or AP.

Requirements

No prior programming knowledge is required

Description

This hands-on course equips learners with practical skills to leverage SQL for data analytics using MySQL. Designed for beginners and intermediate users alike, the course focuses on writing efficient queries to explore, manipulate, and analyze data stored in relational databases.

Through guided exercises and real-world datasets, participants will learn to create and manage database objects, perform data cleaning and transformation, generate descriptive statistics, and build queries that extract actionable insights. Most sessions emphasize experiential learning, allowing students to practice and reinforce each concept directly in MySQL.

The course also introduces best practices for designing scalable data workflows and working with large datasets. Students will gain confidence in using advanced SQL features such as window functions, stored procedures, and indexing techniques. By the end of the course, learners will be able to confidently use SQL to solve analytical problems and support data-driven decision-making in business and research contexts.

Key Topics:

Introduction to relational databases and MySQL environment
Creating and modifying tables
Writing SELECT queries with filtering, sorting, and aggregation
Joining multiple tables
Subqueries and common table expressions
Data cleaning and preparation techniques in SQL
Generating reports and summaries
Advanced query optimization and performance tuning
Analyze the data and get insights for decision making
Error handling

Who this course is for:

Beginners in SQL

SQL for Data Analytics

What you'll learn

Explore related topics

Course content

Introduction to Database management System5 lectures • 1hr 3min

Fundamentals of Structured Query Language5 lectures • 1hr 21min

Aggregate Functions and Clauses5 lectures • 1hr 16min

Queries using Multiple Tables: Joins, CTE, Views4 lectures • 1hr 17min

Stored Procedure2 lectures • 20min

Requirements

Description

Who this course is for: