Welcome to your first SQL lesson! To retrieve data from a SQL database, we use SELECT statements, which are commonly referred to as queries. A query is simply a request that tells the database what data we need, where to find it, and optionally, how to process it before returning the results.

Think of a query as asking a question to your database: "Show me all the customer names" or "What are the top 5 highest-selling products?" The database then responds with the exact information you requested.

🗃️ Understanding Tables and Data

Before we write our first query, let's understand how data is organized in SQL databases.

You can think of a SQL table as representing a type of entity. For example:

• A table named Dogs could store information about different breeds of dogs
• A table named Movies could store information about films
• A table named Customers could store information about your business customers

Table structure:

• Rows represent specific instances of that entity (e.g., a pug, a beagle, a golden retriever)
• Columns define the attributes shared by all instances (e.g., fur color, tail length, breed)

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📝 Writing Your First SQL Query

The simplest query we can write is one that selects specific columns from a table while including all rows. This allows us to retrieve only the information we need without pulling unnecessary data.

🎯 Selecting Specific Columns

SELECT column_name, another_column 
FROM table_1;

This query extracts only the specified columns from table_1 and returns the data as a structured result with rows and columns.

Example:

SELECT title, director 
FROM movies;

This would return just the movie titles and directors, without other information like release year, budget, or ratings.

🌟 Selecting All Columns

If you want to retrieve all columns from a table without listing each one individually, you can use the * wildcard:

SELECT * 
FROM table_1;

This query returns every column and row from the table, making it a quick way to inspect data.

💡 Important Note: In large databases, using SELECT * can be inefficient because it retrieves all data, even columns you don't need. It's generally recommended to specify only the columns you actually need for better performance.

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🔍 When to Use Each Approach

Use specific column selection when:

• You only need certain pieces of information
• Working with large datasets (better performance)
• Creating reports or displays with specific formatting
• You want to reduce data transfer and processing time

Use SELECT * when:

• Exploring a new table to see what data is available
• Working with small datasets
• You genuinely need all the information from the table
• Doing quick data inspection or debugging

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✅ Key Takeaways

• A query retrieves data based on specific conditions and requirements
• Tables store data in a structured format with columns (attributes) and rows (records)
• The SELECT statement allows you to fetch specific columns or all columns from a table
• Specific column selection is more efficient than using SELECT * in most cases
• Use SELECT * wisely - it's great for exploration but can be inefficient with large datasets
• SQL syntax is structured and follows predictable patterns that make it easy to learn

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📝 Exercise Overview

Throughout these lessons, you'll be working with a sample database containing data about Oscar-winning movies. This familiar and fun dataset will help you stay focused on learning SQL without being distracted by complex domain-specific data.

In this first exercise, you'll be working exclusively with the oscar_movies table. As the lessons progress, you'll explore more tables and relationships between them.

Each lesson includes 5–6 hands-on tasks designed to reinforce the concept just covered. These tasks will give you both practical coding experience and a better understanding of how SQL works in real-world scenarios.

Take your time with each one—experiment, break things, and try variations. That's one of the best ways to learn!

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Ready to practice SQL? Try our coding challenges →