This article explores defining and leveraging relationships between tables in structured data to model real-world business transactions.
Welcome back to our series on structured data. In this lesson, we’ll explore how to define and leverage relationships between tables to model real-world business transactions.When you normalize your database, you often end up with one table per entity—Customer, Product, SalesOrder, and so on. Yet, a single transaction typically spans multiple tables. For example, to display the details of a given sales order, you must know:
Each table defines a primary key, a column (or set of columns) that uniquely identifies each row. A foreign key is simply a copy of a primary key added to another table to create a link.
Key Type
Purpose
Example
Primary Key
Unique identifier for a table’s rows
CustomerID
Foreign Key
References a primary key in another table for integrity
As your database grows, frequent JOIN operations can impact query response times.
Excessive joins on large tables without proper indexing can lead to slow queries. Always index foreign key columns and consider query optimization techniques like denormalization or materialized views when necessary.
In the next lesson, we’ll explore strategies—such as indexing, query planning, and denormalization—to optimize relationship performance in large datasets.
