SQL SELECT

🎬 Scenario: Analyzing Netflix Hit Series

You’ve just been hired as a Data Analyst at Netflix! Your first task is to extract insights on the platform’s most successful series.

Your manager, Alex, has asked:

We need a report on our top-performing series, including their ratings, genres, and total viewership. Can you retrieve this data?

To get started, take a look at the netflix_series table, which contains key details:

1. The Basics: SELECT *

The SELECT statement is the foundation of SQL. It’s how we retrieve data from a database.

Syntax

1SELECT * FROM table_name;

Example Query

1SELECT * FROM netflix_series;

Output Example

What’s Happening?

• SELECT * means “Show me everything in this table.”
• While SELECT * works, in real-world data analysis, we often only need specific columns.

2. Selecting Specific Columns

Instead of retrieving all columns, you can specify which columns you need.

Syntax

1SELECT column1, column2 FROM table_name;

Example Query

1SELECT title, genre, rating FROM netflix_series;

Output Example

Why is this better than SELECT *?

• Faster Execution – Only pulls needed columns, reducing unnecessary data.
• More Readable – Avoids cluttering the results with extra columns.

3. Using Aliases (AS) for Readability

Your manager wants to create a report where column names are more readable.
SQL allows you to rename columns using AS.

Syntax

1SELECT column_name AS new_name FROM table_name;

Example Query

1SELECT title AS "Show Name", 
2       genre AS "Category", 
3       rating AS "IMDb Score"
4FROM netflix_series;

Output Example

Why Use Aliases?

• Makes reports more readable for non-technical users.
• Useful when working with complex queries that involve calculations or joins.

✍️ SQL Exercises

Exercise 1: Renaming Columns for a Netflix Series Report

Your manager wants a list of Netflix series along with their release year and total viewership. However, the column names should be more readable for a company report.

Rename the columns as follows:

• title → “Series Name”
• release_year → “Years Released”
• total_views_millions → “Total Views (Millions)”

Write an SQL query to retrieve the requested data.

Expected Output:

Write an SQL query to return the requested data.