SELECT Queries & filtering data - asking the right questions of your data

The SELECT statement is the most frequently used SQL command.
If SQL is a language, SELECT is the sentence you’ll write the most.

In this article, you’ll learn how to:

• Retrieve data from tables
• Filter rows using conditions
• Combine multiple filters
• Think like the database when querying data

This is Part 03 of the SQL from Zero to Pro series.

Table of Contents

• What Does SELECT Do?
• Selecting Columns
• Filtering Rows with WHERE
• Comparison Operators
• Logical Operators
• Filtering Text and Dates
• SQL for Developers vs Analysts
• Practice Exercises
• Conclusion

What does SELECT do?

The SELECT statement retrieves data from one or more tables.

Basic structure

SELECT column_name
FROM table_name;

Example

SELECT name
FROM customers;

What this means:

• Look in the customers table
• Return values from the name column
• Include every row

Selecting columns

Selecting all columns

SELECT * FROM employees;

⚠️ SELECT * is useful for learning, but should be avoided in production queries.

Selecting specific columns

SELECT first_name, last_name
FROM employees;

Benefits:

• Faster queries
• Clear intent
• Less unnecessary data

Filtering rows with WHERE

The WHERE clause filters rows based on a condition.

Basic example

SELECT *
FROM employees
WHERE department = 'HR';

Plain English:

• Look in employees
• Keep only rows where department is HR

Comparison Operators

SQL uses comparison operators to filter values.

Example

SELECT name, price
FROM products
WHERE price > 100;

Logical operators

Logical operators allow you to combine conditions.

AND

SELECT *
FROM employees
WHERE department = 'Sales'
AND salary > 60000;

Both conditions must be true.

OR

SELECT *
FROM employees
WHERE department = 'HR'
OR department = 'Finance';

Either condition can be true.

NOT

SELECT *
FROM users
WHERE NOT active = true;

Negates a condition.

Filtering text and dates

Filtering text

Text values must be wrapped in quotes.

SELECT *
FROM customers
WHERE country = 'UK';

Text comparisons may be case-sensitive depending on collation.

Filtering dates

SELECT *
FROM orders
WHERE order_date >= '2025-01-01';

Using proper date types allows:

• Sorting
• Range filtering
• Date calculations

SQL for Developers vs Analysts

SQL for Developers

Developers focus on:

• Precise filters
• Performance
• Index usage

Common patterns:

• Filtering by primary keys
• Using WHERE clauses in JOINs
• Defensive querying (avoiding unexpected rows)

SELECT *
FROM users
WHERE id = 42;

SQL for Data Analysts

Analysts focus on:

• Exploring datasets
• Finding trends
• Narrowing down results

Common patterns:

• Multiple filters
• Broad queries refined step-by-step
• Temporary exploratory queries

SELECT *
FROM sales
WHERE region = 'EU'
AND sale_date >= '2025-01-01';

Practice exercises

Exercise 1 – Read the Query

Explain what this query does in plain English:

SELECT email
FROM users
WHERE active = true;

Exercise 2 – Write a filtered query

Write a query to:

• Select name and price
• From products
• Where price is less than 50

Exercise 3 – Combine conditions

Write a query that:

• Selects all columns
• From employees
• Where department is Engineering
• And hire date is after 2024-01-01

Bonus practice

Experiment with:

• > vs >=
• Combining AND and OR
• Filtering text vs numeric values

Conclusion

The SELECT and WHERE clauses form the foundation of SQL querying.

If you can:

• Select specific columns
• Filter rows accurately
• Combine conditions logically

You already have the skills needed to query real-world databases.

In the next article (SQL 04), we’ll explore sorting results, limiting rows, and aggregating data, which is where SQL starts answering business-level questions.

Happy querying 🚀

Solutions to the exercises from the article - SQL 03

## **Exercise 1 – Read the query (answer)

SELECT email
FROM users
WHERE active = true;

Plain English explanation

• Look in the users table
• Keep only users whose active status is true
• Return only the email column

This query returns the email addresses of all active users.

Exercise 2 – Write a filtered uery (answer)

SELECT name, price
FROM products
WHERE price < 50;

What this query does

• Retrieves product names and prices
• Excludes products priced at 50 or higher

Exercise 3 – Combine conditions (answer)

SELECT *
FROM employees
WHERE department = 'Engineering'
AND hire_date > '2024-01-01';

Plain English explanation

• Look in the employees table
• Keep only employees in the Engineering department
• Include only those hired after January 1st, 2024

Bonus Practice – Example exploration

Below are a few example queries you might try while experimenting.

Using Greater Than vs Greater Than or Equal To

SELECT *
FROM products
WHERE price >= 100;

Returns products priced at 100 or more, including exactly 100.

Combining AND and OR

SELECT *
FROM employees
WHERE department = 'HR'
OR department = 'Finance'
AND active = true;

⚠️ Important: AND is evaluated before OR.

To make the logic explicit:

SELECT *
FROM employees
WHERE (department = 'HR' OR department = 'Finance')
AND active = true;

Filtering text vs numeric values

-- Text comparison
SELECT *
FROM customers
WHERE country = 'UK';

-- Numeric comparison
SELECT *
FROM orders
WHERE total_amount > 500;

Text values are quoted, numeric values are not.

Key takeaways

• SELECT chooses columns
• FROM chooses the table
• WHERE filters rows
• Comparison and logical operators let you narrow results precisely

If you can confidently read and write these queries, you’re officially querying like a SQL user — not just memorising syntax.

Next up: SQL 04 – ORDER BY, LIMIT, and Aggregations 🚀