Knowledge content of unstructured data

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An example is an email: the subject, recipient, and sender are known, but the rest of the data is not.

Structured Data
Structured data always have a predefined format of rows and columns (e.g. CRM systems). So, on one hand, they are easy to find/process with the help of SQL databases, but, if they are built on a relational model, they also avoid duplication of information (data redundancy).
Examples of structured data are, for example, barcodes, log statistics or customer databases. Excel spreadsheets also contain manually created, structured data.

The knowledge stored in unstructured data instagram database is initially "richer" than knowledge stored in structured form. This is due to the fact that often more can be inferred from the context than from structured data (e.g., the sentiment and context of an email). With structured data, the detailed context is often lost. As a result, unstructured data is harder to interpret and is often a case of data scientists.

One issue that is often confused is between big data and unstructured data. Big data is not necessarily unstructured, it can also be in a structured form (for example, Netflix's streaming data). At the same time, there is also unstructured data that is not considered big data, such as individual media assets such as images or videos.