What is the difference between structured and unstructured data?

Structured data refers to information that is organized in a defined manner, typically in rows and columns, which makes it easily searchable and analyzable using traditional data tools and databases. This format allows for straightforward querying through languages like SQL. For example, data stored in relational databases, such as customer records, financial transactions, or inventory lists, is structured because it adheres to a specific schema.

On the other hand, unstructured data lacks this predefined organization and does not fit neatly into a database table format. This category includes a wide array of information, such as emails, social media posts, images, videos, and more. While it can be analyzed, searching through unstructured data often requires more advanced techniques like natural language processing and machine learning, making it less convenient to retrieve specific insights compared to structured data.

The distinction in searchability is essential, as it highlights the practical applications and challenges associated with managing both types of data.