SQL for Data Analytics Course Notes

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Course Overview

• This course covers SQL for data analytics.
• Aimed at beginner and advanced users.
• Structured to master SQL basics and build to advanced techniques.

Importance of SQL

• SQL is a key skill in data science.
• SQL is the most sought-after skill in job postings for:
  • Data Analyst: Number one required skill.
  • Data Engineer: Number one required skill.
  • Data Scientist: Second most important skill after Python.

Course Structure

Chapters

1. Basics of SQL

   • Key concepts of SQL databases.
   • Basic SQL queries including SELECT, FROM, WHERE, GROUP BY, ORDER BY, LIMIT.
   • Introduction to relational vs. non-relational databases.
   • Understanding CRUD operations: Create, Read, Update, Delete.

2. Advanced Techniques

   • Setting up a local database using Postgres.
   • Writing complex queries with CTE and subqueries.
   • Understanding joins: left join, inner join, right join, full outer join.
   • Using date functions and handling NULL values.
   • Aggregation functions: SUM, COUNT, AVG, MIN, MAX.

3. Capstone Project

   • Solve a real-world problem using SQL.
   • Analyze top skills and jobs in the data science industry.
   • Showcase project on GitHub.

Key SQL Concepts

SQL Basics

• SQL: Structured Query Language for managing data in relational databases.
• Databases: Collections of structured data; types include relational (tables) and non-relational.
• CRUD Operations: Basic operations to manipulate data.

Advanced SQL Techniques

• Joins: Combine rows from two or more tables based on a related column.
• CTEs (Common Table Expressions): Temporary result sets that can be referenced within SELECT, INSERT, UPDATE, or DELETE statements.
• Subqueries: Queries nested inside other queries.
• Date Functions: Manipulate and extract data from date columns.
• Aggregation Functions: Summarize data using functions like SUM, COUNT, and AVG.

Key Queries and Examples

Top Paying Data Analyst Roles

• Identify the top 10 highest paying roles.
• SQL query to find jobs with salary greater than a specific amount.

Skill Demand Analysis

• Analyze skills required for the highest paying roles.
• SQL query to join job postings with skills and aggregate skills by demand.

Most In-Demand Skills

• SQL query to find the most in-demand skills for Data Analysts.
• Use GROUP BY and ORDER BY to summarize results.

Final Project

• Showcase skills learned throughout the course.
• Use GitHub for version control and project management.
• Create and present a detailed README file.

Conclusion

• SQL is essential for data analysis and job functions in data science.
• Mastery of SQL opens up numerous opportunities in data analytics.