Data Analytics Module 2

The Basic Structured Queried Language (SQL)

Learning Outcomes: Data helps us make decisions in everyday life and in business. In this first part of the course, you’ll learn how data analysts use data analytics and the tools of their trade to inform those decisions. 

  • Program Description and course syllabus
  • Introduction to the course
  • Helpful resources to get started
  • What is Data Ecosystem
  • How Data Informs better decisions

SQL Joins

Learning Outcomes: In this part of the course, you’ll learn to Create Joins, Use Primary and Foreign Keys, Integrate Aliases, Evaluate Various Join Types, and Integrate Filters with Joins.

  • Introduction to Joins
  • Primary and Foreign Keys
  • Alias
  • Left and Right Joins
  • Other Joins types
  • Joins and Filtering


SQL Aggregation

Learning Outcomes: The combination of JOINs and Aggregations is one of the reasons SQL is such a powerful tool. In this lesson, we will deal with NULL values, and also create aggregations in our SQL queries including COUNT, SUM, MIN & MAX etc.

  • Introduction to Aggregation
  • NULLs and Aggregation
  • COUNT and NULLs
  • SUM
  • MIN & MAX
  • AVG

SQL Subqueries and Temporary Tables

Learning Outcomes: In this part of the course, we will cover subqueries, a fundamental advanced SQL topic. The lesson will focus on Creating subqueries to solve real-world problems, differentiating between Subqueries and Joins, considering the tradeoffs to using subqueries, and implementing the best subquery Strategy.

  • Introduction to Subqueries
  • Subqueries in Real-world application
  • Subqueries Vs Joins
  • Subquery Basics
  • Subquery Placement
  • Subquery Formatting
  • Subquery Dependencies
  • SQL Views
  • Subquery Mania
  • Subquery Tradeoff
  • Subquery Strategy

SQL Data Cleaning

Learning Outcomes: In this part of the course, you’ll learn how to clean and re-structure messy data, convert columns to different data types, manipulate NULLs with some handy tricks.

  • Introduction to SQL Data Cleaning
  • Data Cleaning Real-world Application
  • Data Cleaning Strategy
  • Commonly Used Data Functions
  • Advanced Cleaning Functions

Tools Required

  • Microsoft excel or Google sheet 
  • MySQL
  • Power BI



  • Ability to use the computer
  • Availability of internet

Course Details














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