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Learn SQL in the Age of AI

Exploring Table Structures

Learn how to explore table structure and apply limitations while fetching table records.

We'll cover the following...

Step 1: Start with curiosity

Previously, you asked: Who are the employees?

This query returns a complete list of all employee records.

Now ask a deeper question:

What kind of data does this table contain?

This isn’t about values yet, it’s about structure.

Prompt: Write a SQL query that shows the structure (columns and their data types) of the table employees.

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5 Prompts Remaining
Prompt AI WidgetOur tool is designed to help you to understand concepts and ask any follow up questions. Ask a question to get started.

Step 2: Run and observe

AI might return one of these, depending on the SQL flavor:

MySQL
DESCRIBE employees;

 Run the query. You’ll see something like:

Field

Type

Null

Key

Default

id

INT

NO

PRI

—

first_name

VARCHAR(50)

YES

—

last_name

VARCHAR(50)

YES

—

department

VARCHAR(50)

YES

—

salary

DECIMAL(10,2)

YES

—

Step 3: Interpret together

Let’s unpack what you’re seeing.

  • Columns (like first_name): types of information.

  • Rows: Each record in the dataset (one employee).

  • Type: What kind of data fits here:

    • INT → whole numbers

    • VARCHAR → text

    • DECIMAL → numbers with decimals

  • Schema → the table’s full design: column names, types, constraints.

Ask yourself:

  • Why might knowing data types matter before writing a query?

  • What could go wrong if you tried to sum a VARCHAR column?

Step 4: Ask the table questions

Let’s explore one more idea: sometimes it helps to peek at the first few rows to match columns to values.

Prompt: Write a SQL query that shows the first 5 rows from the employees table.

Powered by AI
5 Prompts Remaining
Prompt AI WidgetOur tool is designed to help you to understand concepts and ask any follow up questions. Ask a question to get started.

AI should respond with:

MySQL
SELECT *
FROM employees
LIMIT 5;

Run it. Now connect the structure, values:

  • id: unique number per employee.

  • department: text labels that repeat.

  • salary: numbers you can aggregate later.

That mental link, column to data type to value, is the foundation of data literacy.

Step 5: Your turn to tweak

Try this small edit yourself: Change the query to show only two columns from the table employees: first_name and salary, but restrict the viewing to only top 3 rows of the table.

MySQL
-- Write your SQL query here:

Notice how you used what you learned in 1.1 (SELECT columns) and what you now know about the schema to choose meaningful fields.

Quick recap

Concept

What It Means

Example

Table

A collection of related data (like a spreadsheet)

employees

Row

One record/observation

One employee

Column

A single attribute

salary or department

Schema

Blueprint describing all columns and types

use DESCRIBE employees;

Practice prompts

Use the AI Prompt Widget to ask:

  1. Show me the columns and data types of the employees table.

  2. Show me the first 3 rows of the employees table.

  3. How can I tell if a column is numeric or text?

Then adjust one query manually to limit or expand results.

Reflect before moving on

  • How do column names and types help you decide what question to ask next?

  • Which columns seem quantitative (numbers you can measure)?

  • Which seem categorical (labels you can group)?

You’ve completed Lesson 2. You can now inspect a table’s schema to understand its structure, connect what you see in SQL to what the data means, and choose columns confidently for your next query.