AI Glossary
Structured Data
Data that is organized into a predefined format, making it easy to store, search, and analyze.
Structured Data
Overview
Not all information is organized in the same way.
Some information follows a clear structure, making it easy for both people and computers to understand.
This type of information is known as structured data.
Structured data is organized into predefined formats, often using rows, columns, tables, and databases. Each piece of information has a specific location and meaning.
A helpful way to think about structured data is a spreadsheet.
Every row contains information about a particular item, and every column represents a specific category. Because everything is organized consistently, finding and analyzing information becomes much easier.
Organizations use structured data extensively for business operations, reporting, analytics, and machine learning.
Examples include customer databases, financial records, inventory systems, employee directories, and sales reports.
Many AI systems rely on structured data because it can be processed efficiently and analyzed at scale.
Although structured data is important, it represents only part of the information organizations generate. Increasingly, AI systems must also work with Unstructured Data.
Why It Matters
Structured data makes information easier to organize, analyze, and use within AI systems.
Real-World Example
A customer database containing names, addresses, account numbers, and purchase history is an example of structured data.