This is an intermediate Data Analytic course where students will be introduced into how SQL is used in data analytics.
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
GROUP BY
DISTINCT
HAVING
DATE FUNCTION
CASE STATEMENT
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.