Imagine you are managing a large library. Each book has a title, an author, a genre, and a date it was added to the collection. To keep track of everything, you might use a spreadsheet where each row represents a book and each column represents a detail about the book. This is similar to how data is organized in a relational database. In databases, tables store information in a structured way, much like a spreadsheet or a library catalog. Each table is made up of rows (also called records) and columns (also called fields). This structure allows you to store, organize, and retrieve information quickly and efficiently. For example, a business might use a table to keep track of its customers, with each row representing a different customer and each column storing information such as the customer's name, city, and signup date.

This SQL statement creates a table called customers. The CREATE TABLE command tells the database that you want to make a new table. Inside the parentheses, you define each column:

• The id column is of type SERIAL, which means it will automatically generate a unique number for each customer; it is also set as the PRIMARY KEY, ensuring each row is uniquely identified.
• The name column uses the VARCHAR(100) data type, which stores text up to 100 characters, and NOT NULL means this field cannot be left empty.
• The city column is also a VARCHAR(100) and cannot be empty.
• The signup_date column uses the DATE data type to store the date each customer signed up, and must also be filled in for every row.

Each column definition specifies the type of data it can hold and any rules about whether it can be empty or must be unique. This structure helps keep your data organized and ensures you always have the information you need for each customer.