Any data that can be stored, accessed and processed in the form of fixed format is termed as a 'structured' data. Over the period of time, talent in computer science has achieved greater success in developing techniques for working with such kind of data (where the format is well known in advance) and also deriving value out of it. It refers to highly organized information that can be readily and seamlessly stored and accessed from a database by simple search engine algorithms.
Any data with the unknown form of the structure is classified as unstructured data. Or it can also be said as Unstructured data refers to the data that lacks any specific form or structure whatsoever. In addition to the size being huge, unstructured data poses multiple challenges in terms of its processing for deriving value out of it. A typical example of unstructured data is a heterogeneous data source containing a combination of simple text files, images, videos, etc.
Semi-structured is the third type of big data. Semi-structured data can contain both forms of data. We can see semi-structured data as a structured in form but it is actually not defined with e.g. a table definition in relational DBMS.it refers to the data that although has not been classified under a particular repository (database), yet contains vital information or tags that segregate individual elements within the data.