SQL for Data Analysis: Advanced SQL Querying Techniques
Size: 3.55 GB

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

HOMEPAGE – https://www.udemy.com/course/sql-advanced-queries/

Free Download Link-

Note: Comment below if you find the download link dead.


0 Comments

Leave a Reply

Your email address will not be published. Required fields are marked *