SELECT and FROM Basics

Being Specific About What You Want

In the last lesson, you learned that SELECT tells the database which columns to return. Simple enough. But there's more nuance here than you might expect, and getting it right matters for both performance and readability.

Why SELECT * is a Bad Habit

When you're exploring a new table, SELECT * is fine. It shows you everything, which helps you understand what you're working with.

SELECT * FROM techcorp_workforce;

But in real work — queries that run in dashboards, reports, or production systems — SELECT * causes problems:

• Performance — you're pulling data you don't need. On big tables, this slows everything down.
• Clarity — someone reading your query can't tell what data actually matters.
• Fragility — if someone adds a column to the table, your query's output changes unexpectedly.

Get in the habit of specifying columns:

-- Instead of SELECT *, specify what you need:
SELECT
  id,
  first_name,
  last_name,
  department
FROM techcorp_workforce;

Choosing Column Order

SELECT
  order_details,
  cust_id,
  total_order_cost
FROM orders;

This seems trivial, but it matters when you're building reports or exporting data. Put the most important columns first.

Renaming Columns with Aliases

Database column names like employee_id or created_at make sense for developers. They're consistent, predictable, and avoid spaces or special characters. But when you're building a report or dashboard for stakeholders, you want something more readable.

That's what aliases are for. Use AS to rename a column in your output:

When Aliases Are Required

Aliases aren't just cosmetic. Sometimes you need them. When you create a calculated column, it has no name until you give it one.

Basic Arithmetic in SELECT

SQL supports standard math operators directly in your SELECT clause:

• + addition — example: salary + 5000 adds a bonus
• - subtraction — example: salary - tax calculates net pay
• * multiplication — example: price * quantity gets a total
• / division — example: salary / 12 converts annual to monthly

Combining Text with Concatenation

Sometimes you need to combine text from multiple columns — for example, creating a full name from first_name and last_name.

String Concatenation

SELECT
  CONCAT(first_name, ' ', last_name) AS full_name
FROM employees;

The AS Keyword is Optional (But Use It Anyway)

SQL lets you skip the AS keyword:

SELECT
  first_name "First Name"
FROM techcorp_workforce;

This works, but it's harder to read. The explicit AS makes your intent clear. Don't skip it.

Removing Duplicates with DISTINCT

Sometimes you want to know what values exist in a column, not see every row. SELECT DISTINCT removes duplicate values from your results.

Let's look at the orders table:

Without DISTINCT, you'd see duplicate order details:

DISTINCT with Multiple Columns

When you use DISTINCT with multiple columns, it removes rows where the entire combination is duplicated:

This returns unique customer-product pairs. So if customer 3 ordered Shoes twice, you'd only see that combination once.

A Quick Note on Data Types

Every column in a database has a data type. You don't need to memorize these, but it helps to know the main categories:

• Text — VARCHAR, TEXT, CHAR — used for names, emails, descriptions
• Numbers — INTEGER, DECIMAL, FLOAT — used for counts, amounts, percentages
• Dates — DATE, TIMESTAMP, DATETIME — used for when things happened
• Boolean — TRUE/FALSE — used for yes/no flags

Why does this matter? Because you can't do math on text, and you can't search for patterns in numbers (well, you can, but you shouldn't). Understanding data types helps you avoid weird errors and choose the right functions.

We'll cover type-specific operations in later modules. For now, just know that the database handles different data types differently.

Practice: Selecting Columns with Aliases

Let's practice with the restaurant inspections data:

Common Mistakes

Forgetting the comma between columns

-- This will give an error:
SELECT
  first_name
  last_name
FROM techcorp_workforce;
-- SQL thinks you're aliasing first_name as "last_name"

-- What you meant:
SELECT
  first_name,
  last_name
FROM techcorp_workforce;

Trailing comma after the last column

-- This will give an error:
SELECT
  first_name,
  last_name, -- extra comma
FROM techcorp_workforce;

-- Correct:
SELECT
  first_name,
  last_name
FROM techcorp_workforce;

Misspelling column names

SQL won't guess what you meant. If the column is first_name and you type firstname, you'll get an error. Check your spelling, and remember that most databases are case-sensitive for column names.

Key Takeaways

• Specify columns instead of using SELECT * in production queries.
• Column order in SELECT determines output order.
• Use AS to create readable column aliases — always write it explicitly.
• DISTINCT removes duplicate rows from results — it applies to the entire row, not just the first column.
• Data types determine what operations you can perform on columns.

What's Next

Now you know how to get data out of a table. But so far, you're getting all rows. In the next lesson, you'll learn to filter data with WHERE — which is when SQL starts to feel actually powerful.