Summary Analytics (MIN, MAX, AVG, GROUP BY)

Final Quiz

Dhaval Patel

Data Entrepreneur | YouTuber | Ex - Bloomberg, Nvidia

I have 17 years of experience in Programming and Data Science working for big tech companies like NVIDIA and Bloomberg. I also run a famous YouTube channel called Codebasics where I pursue my passion for teaching. Codebasics is one of the top channels on YouTube when it comes to data science, machine learning, data structures, etc. I firmly believe that “Anyone can code” and I use analogies, simple explanations, and step-by-step storytelling to explain difficult concepts in such a way that even a high school student can understand them easily.

Hemanand Vadivel

Ex- Data Analytics Manager, 8+ Years in Europe, Microsoft Certified, Certified Supply Chain Professional

I’m a mechanical engineer who transitioned to a full time Data & Analytics manager in the UK & Germany by teaching myself Power BI, excel & anything else that was required to solve the problem. I have worked with complex data across Supply Chain, Sales, Marketing, Revenue Management, Finance and HR functions over the last 8 years to deliver effective solutions. To me, Analytics is an extra sensory organ that anyone can develop to become a superhuman at work. I have conducted several workshops and internal training to help non-technical people to become superhuman at work and now, really excited for this opportunity to share all that knowledge with you in this course.

Summary Analytics (MIN, MAX, AVG, GROUP BY)

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Summary Analytics (MIN, MAX, AVG, GROUP BY)

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In this lecture, we will cover,

1. Basic analytics functions: MIN, MAX, AVG, COUNT

2. GROUP BY

MySQL functions and operators documentation: [https://dev.mysql.com/doc/refman/8.0/en/built-in-function-reference.html]

No FAQ Available.

Contents

1. Course Overview

Who can Enroll in this Course? Any Prerequisites?

What Type of Computer do I Need for this Course?

Course Outline

2. Enhance your Learning Experience

Video Resolution

Join Discord

3. Introduction

How Learning SQL can Help You in Your Career

Who is Peter Pandey?

Peter Pandey’s Early Life and SQL

4. SQL Basics: Data Retrieval - Single Table

Install MySQL: Windows

Install MySQL: Linux, Mac

Import Movies Dataset in MySQL

Retrieve Data Using Text Query (SELECT, WHERE, DISTINCT, LIKE)

Exercise - Retrieve Data Using Text Query (SELECT, WHERE, DISTINCT, LIKE)

Retrieve Data Using Numeric Query (BETWEEN, IN, ORDER BY, LIMIT, OFFSET)

Exercise - Retrieve Data Using Numeric Query (BETWEEN, IN, ORDER BY, LIMIT, OFFSET)

Summary Analytics (MIN, MAX, AVG, GROUP BY)

Exercise - Summary Analytics (MIN, MAX, AVG, GROUP BY)

HAVING Clause

Calculated Columns (IF, CASE, YEAR, CURYEAR)

Exercise - Calculated Columns (IF, CASE, YEAR, CURYEAR)

The Data God’s Blessing

Quiz

5. SQL Basics: Data Retrieval - Multiple Tables

Why do We Need Multiple Tables?

SQL Joins (INNER, LEFT, RIGHT, FULL)

Exercise - SQL Joins (INNER, LEFT, RIGHT, FULL)

Cross Join

Analytics on Tables

Join More Than Two Tables

Exercise - Join More Than Two Tables

Quiz

6. SQL Basics: Complex Queries

Subqueries

ANY, ALL Operators

Co-Related Subquery

Exercise: Subqueries

Common Table Expression (CTE)

CTE Benefits & Other Applications

Exercise: CTE

Peter Pandey Flexes his SQL Skills

Quiz

7. SQL Basics: Database Creation & Updates

Database Normalization and Data Integrity

Entity Relationship Diagram (ERD)

Mentor Talk: Art of Googling

Data Types: Numeric (INT, DECIMAL, FLOAT, DOUBLE)

Data Types: String (VARCHAR, CHAR, ENUM)

Data Types: Date, Time (DATETIME, DATE, TIME, YEAR, TIMESTAMP)

Data Types: JSON, Spatial (JSON, GEOMETRY)

Luck Favors the LinkedIn Post

Primary key

Foreign Key

Create a Database From an Entity Relationship Diagram - ERD

Import Data From a CSV File Into a Database

Insert Statement

Update and Delete

I Need a Favour

Expect the Unexpected: The Intermission Scene

Quiz

8. AtliQ Hardware & Problem Statement

The Rise of Databases at AtliQ

Relational vs No-SQL Database

AtliQ Hardware’s Business Model

Profit & Loss Statement

ETL, Data Warehouse, OLAP vs OLTP, Data Catalog

Fact vs Dimension Table, Star vs Snowflake Schema, Data Import

Simplified: What is Kanban?

Quiz

9. SQL Advanced: Finance Analytics

Backlog Grooming Meeting: Gross Sales Report

User-Defined SQL Functions

Exercise: User-Defined SQL Functions

Gross Sales Report: Monthly Product Transactions

Gross Sales Report: Total Sales Amount

Exercise: Yearly Sales Report