Welcome to SQL for Data Analytics! SQL, or Structured Query Language, is the essential tool for working with data in relational databases. A database contains multiple tables, each storing structured data in rows and columns. Through SQL queries, we can extract valuable insights and perform complex analytics on this data.
Let's explore basic SQL syntax. The SELECT statement is fundamental - it retrieves data from database tables and specifies which columns to display. The WHERE clause filters rows based on conditions using comparison and logical operators. Here we select customers over 25 years old living in New York, returning their name, age, and city.
Moving to intermediate SQL, we explore JOINs and aggregation. JOIN operations combine data from multiple tables - INNER JOIN returns only matching records, while LEFT and RIGHT JOINs include all records from one table. GROUP BY groups rows by column values, enabling aggregate functions like COUNT and AVG. The HAVING clause filters groups based on aggregate conditions.
Advanced SQL introduces powerful features like window functions and Common Table Expressions. Window functions like ROW_NUMBER, RANK, and LAG operate on sets of rows related to the current row, using PARTITION BY to group data and ORDER BY to sort within groups. CTEs with the WITH clause create temporary named result sets, making complex queries more readable and maintainable.
Congratulations on completing your SQL for data analytics journey! You've mastered the fundamentals from basic SELECT statements to advanced window functions and CTEs. These skills form the foundation for extracting meaningful insights from data and solving complex analytical challenges in any industry.