Practical Sql For Data Analysis

Learn how to create and analyze data in SQL practically

What you'll learn

Database modeling

Understanding Primary and foreign key concept

Creating databases using MYSQL Workbench and Query

Creating and managing tables – data type, length, null and default constraint.

Creating and managing Table relationship – one to many, one to one and many to many relationship

Cascading update and cascading delete concept

Working with data – Insert, select, update, delete

Creating and managing Indexes – clustered Index and none clustered index

Creating and managing views

Creating and managing triggers

Creating and managing stored procedure

Creating and managing events

Analyze data with SQL

Requirements

No prior experience in SQL needed. You will learn everything in SQL from beginner to advanced level

Description

Master the art of harnessing the power of Structured Query Language (SQL) to analyze and manage data in this comprehensive course, "SQL for Data Analysis." Designed for aspiring data analysts, business professionals, and tech enthusiasts, this course will equip you with the skills to create, manage, and analyze relational databases effectively.The journey begins with understanding the fundamentals of database modeling, where you'll learn to design robust databases with logical structures. You’ll gain a strong grasp of primary and foreign key concepts, essential for building and maintaining database integrity.Using tools like MySQL Workbench and SQL queries, you’ll create databases from scratch and manage tables with precision, focusing on key aspects like data types, length, null values, and default constraints. Explore table relationships by implementing one-to-one, one-to-many, and many-to-many relationships, ensuring seamless data connections. Dive deeper into advanced techniques like cascading updates and deletes, which automate relationship management.This course emphasizes working with data through essential commands: INSERT, SELECT, UPDATE, and DELETE, ensuring you can manipulate and retrieve data efficiently. Enhance database performance by learning to create and manage indexes—both clustered and non-clustered.Expand your SQL expertise by mastering views, which streamline data analysis, and triggers, which automate actions based on specified events. You’ll also delve into crafting stored procedures and scheduling events for effective database management.Finally, sharpen your analytical skills by exploring techniques to extract actionable insights from data using SQL.By the end of this course, you’ll be equipped with practical skills to design, manage, and analyze databases, paving the way for a successful career in data analysis or database management.

Overview

Section 1: Introduction to SQL

Lecture 1 Introduction

Lecture 2 Data Modeling

Lecture 3 Data Normalization

Lecture 4 Download and Install SQL Server

Lecture 5 Create a database and import tables

Lecture 6 What is a database ?

Lecture 7 Database object - Table

Lecture 8 Database object - Index

Lecture 9 Database object - View

Lecture 10 Database object - Triggers

Lecture 11 Create primary key on the branch table

Lecture 12 Create primary keys on other tables

Lecture 13 Import returns table and set primary

Section 2: Data Manipulation Language

Lecture 14 Module introduction

Lecture 15 DML - SELECT Command

Lecture 16 DML - INSERT Command

Lecture 17 DML - UPDATE Command

Lecture 18 DML - DELETE Command

Section 3: Data Definition Language

Lecture 19 Module introduction

Lecture 20 DDL - CREATE Command

Lecture 21 DDL - ALTER Command

Lecture 22 DDL - DROP Command

Lecture 23 DCL Commands

Section 4: Basic SQL Statement

Lecture 24 Module introduction

Lecture 25 How to work with the SELECT Statement

Lecture 26 SELECT Statement with WHERE Clause

Lecture 27 SELECT with WHERE and AND Clauses

Lecture 28 SELECT With WHERE and IN Clauses

Lecture 29 How to work with SELECT and DISTINCT

Lecture 30 Subquery in the WHERE Clause

Section 5: Aggregate Functions

Lecture 31 Module introduction

Lecture 32 Aggregate function - Count

Lecture 33 Aggregate function - SUM

Lecture 34 Aggregate function - Average

Lecture 35 Aggregate function - MIN

Lecture 36 Aggregate function - MAX

Lecture 37 Math operators and calculations

Section 6: Joins in SQL

Lecture 38 Module introduction

Lecture 39 Implementing inner join

Lecture 40 Implementing left join

Lecture 41 Implementing right join

Lecture 42 Implementing full join

Lecture 43 Join multiple tables in SQL

Section 7: Data Cleaning, Analysis and Reporting in SQL

Lecture 44 Module introduction

Lecture 45 Data transformation - Sales OrderDate

Lecture 46 Data transformation - Products table

Lecture 47 Data transformation - Customers table

Lecture 48 Sales KPI - Revenue-Expenses-Profit-Profit Margin

Lecture 49 Sales KPI correction

Lecture 50 Monthly Revenue Trend Analysis

Lecture 51 Monthly Revenue Trend Analysis explanation

Lecture 52 Revenue by branch analysis

Lecture 53 Revenue by Product Category

Lecture 54 Revenue by top 5 products analysis

Lecture 55 Revenue by customer gender

Lecture 56 SQL Analysis Report

For aspiring data Analysts and data scientist who wants a solid foundation in SQL. This course is also suitable for software and data engineer who need deeper knowledge in SQL.