What distinguishes structured data from unstructured data?

Structured data is characterized by its organization into a defined schema, which typically includes specific fields and formats that make it easily accessible and analyzable, such as in relational databases. This clear structure allows for straightforward querying and data manipulation using structured query language (SQL) or similar database management tools.

In contrast, unstructured data lacks this organized format, making it more challenging to collect, process, and analyze. Examples of unstructured data include emails, videos, social media posts, and other forms of content that do not conform to a predefined model. The absence of a clear format or schema in unstructured data means that specialized techniques, such as natural language processing or machine learning algorithms, are often required to extract meaningful information from it.

Therefore, the main distinction lies in the presence of a defined organization in structured data versus the absence of such organization in unstructured data, which significantly impacts how this information is stored, accessed, and analyzed.