The SELECT statement retrieves data from database tables. It's the foundation of all SQL queries.

Key Concepts:

• SELECT specifies which columns to retrieve
• FROM indicates which table(s) to query
• You can select specific columns or all columns (*)
• Results are returned as a table of rows

Basic Syntax:

SELECT column1, column2, ... FROM table_name;
SELECT * FROM table_name;  -- Get all columns

Common Use Cases:

• Retrieving customer information
• Generating reports
• Analyzing data patterns
• Building API responses

Let's start with a simple query to get customer data.

Write a query that:

• Retrieves all columns (*)
• From the customers table
• Returns all rows

Tips:

• Use SELECT * to get all columns
• Always specify the table name after FROM
• End your query with a semicolon (optional in SQLite)
• Consider performance with large tables

Often, you only need certain columns, not the entire row.

Write a query that gets:

• Customer names (name column)
• Email addresses (email column)
• From the customers table

Benefits of Selecting Specific Columns:

• Reduces data transfer
• Improves query performance
• Makes results more focused
• Saves client memory

Best Practice: Only select the columns you actually need.

Aliases give columns more readable or specific names in the results.

Write a query that:

• Gets the product name as "Item"
• Gets the price as "Cost"
• From the products table

Use Cases for Aliases:

• Making results more readable
• Avoiding column name conflicts
• Clarifying calculated fields
• Matching API requirements

Syntax: Use AS or just a space between the column and alias.

You can perform calculations in your SELECT statement.

Write a query that gets:

• Product name
• Price
• Price with 20% discount (price * 0.8)
• From the products table

Common Calculations:

• Arithmetic operations (+, -, *, /)
• Date calculations
• String concatenation
• Conditional logic

Note: Calculated fields can also have aliases for clarity.

The DISTINCT keyword removes duplicate values from results.

Write a query that gets:

• Unique countries
• From the customers table
• Using DISTINCT

Use Cases for DISTINCT:

• Finding unique categories
• Removing duplicate entries
• Analyzing data distribution
• Cleaning data

Note: DISTINCT considers NULL as a value and will return it once if present.

Let's combine multiple concepts in one query.

Write a query that:

• Gets unique product categories
• Shows the average price per category
• Aliases the average as "avg_price"
• Rounds the average to 2 decimal places

Advanced Techniques:

• Combining DISTINCT with calculations
• Using built-in functions (ROUND)
• Creating meaningful aliases
• Organizing complex queries

This brings together several concepts we've learned.