What distinguishes structured data from unstructured data?

Structured data is characterized by its highly organized nature, which allows it to be easily searchable and analyzable. It is typically arranged in a predefined model or format, such as rows and columns in databases, making it easily accessible for various types of analysis. This organization means structured data can be readily used in query languages like SQL, where specific fields can be identified and extracted efficiently.

In contrast, unstructured data does not conform to a specific format or structure, which makes it more challenging to process and analyze. While this type of data can contain valuable information, it often requires additional processing to extract meaningful insights. Examples of unstructured data include text documents, images, and videos, which do not fit neatly into a predefined schema.

This distinction underscores the importance of structured data in analytical processes, as its organization directly supports efficient data management and retrieval.