SQL for Data Analysis: Advanced SQL Querying Techniques
What you'll learn
- Conduct multi-table analysis using JOINs and learn variations like self joins, cross joins, and more
- Learn to work with nested queries by writing subqueries and common table expressions (CTEs), and understand the best use cases for each
- Use window functions to perform calculations across a set of rows and learn various function options and applications
- Discover the many SQL functions that can be applied to fields of numeric, datetime, string, and NULL data types
- Apply advanced querying techniques to common data analysis scenarios, including pivoting data, rolling calculations, and more
Requirements
- Any SQL Editor (we'll walk you through the install process specifically for MySQL Workbench)
- If you are new to SQL, we strongly recommend taking Maven Analytics' Beginner MySQL Business Intelligence course first
Description
This is a hands-on, project-based course designed to help you move beyond the "Big 6" clauses into advanced querying techniques.
We’ll start by reviewing the basics and conducting multi-table analyses, including basic joins, self-joins, cross-joins, and unions.
Next, we’ll cover different ways of working with nested queries by writing subqueries and common table expressions, or CTEs. We’ll walk through examples of subqueries within the various clauses, rewrite subqueries as CTEs, introduce recursive CTEs, and compare these techniques to other options like temporary tables and views.
From there, we’ll break down each component of a window function and review common window functions like ROW_NUMBER, RANK, FIRST_VALUE, LEAD, and LAG. We’ll also cover general functions for working with different data types in SQL, including numeric, datetime, string, and NULL functions.
Last but not least, we’ll take the concepts we’ve learned and use them across a series of common data analysis applications. We’ll deal with duplicate values, apply special value filters, perform rolling calculations, and more.
To wrap up the course, you’ll work on a project as a Data Analyst Intern for Major League Baseball, and use advanced SQL querying techniques to track how player stats like salary, height, and weight have changed over time and across different teams.
COURSE OUTLINE:
SQL Basics Review
Review the big 6 clauses of a SQL query along with other commonly used keywords like LIMIT, DISTINCT, and more
Multi-Table Analysis
Review JOIN basics (INNER, LEFT, RIGHT, OUTER) and introduce variations like self joins, CROSS JOINs, and more
Subqueries & CTEs
Learn how to write subqueries and Common Table Expressions and understand the best situations for using certain techniques
Window Functions
Introduce window functions to perform calculations across a set of rows and discuss various function options and applications
Functions by Data Type
Discover the many SQL functions that can be applied to fields of numeric, datetime, string, and NULL data types
Data Analysis Applications
Apply advanced querying techniques to common data analysis scenarios, including pivoting data, rolling calculations, and more
Final Project
Leverage everything you've learned to track how Major League Baseball (MLB) player statistics have changed over time and across different teams in the league
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Ready to dive in? Join today and get immediate, LIFETIME access to the following:
8 hours of high-quality video
21 homework assignments
6 quizzes
4-part final project
Advanced SQL Querying ebook (150+ pages)
Downloadable project files & solutions
Expert support and Q&A forum
30-day Udemy satisfaction guarantee
If you’re an analyst, data scientist, or BI professional looking to master advanced querying with SQL, this is the course for you.
Happy learning!
-Alice Zhao (Author, SQL Pocket Guide and Data Science Instructor, Maven Analytics)
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Who this course is for:
- Analysts or BI professionals looking to analyze data stored in relational database systems
- SQL users who want to develop advanced querying skills
- Anyone looking for a hands-on, practical, and highly engaging way to master SQL for advanced data analysis
Instructors
Maven Analytics empowers everyday people with life-changing data skills.
Named one of the top EdTech companies revolutionizing the industry, our unique Guided Learning model helps individuals and teams learn new skills, showcase their work, and connect with experts around the world.
We've helped 2,000,000+ students build job-ready skills, master tools like Excel, SQL, Power BI, Tableau and Python, and accelerate their data careers.
Start learning for free!
Alice Zhao is a data scientist who is passionate about teaching and making complex things easy to understand.
She is a lecturer for Northwestern University's Machine Learning and Data Science graduate program where she teaches Python, R, Data Warehousing and Data Visualization.
She is the author of the book, SQL Pocket Guide, 4th Edition (O'Reilly) and has the most popular Natural Language Processing in Python tutorial on YouTube, with 1.2 million views.
She has an M.S. in Analytics and B.S. in Electrical Engineering, both from Northwestern University.