Semi-structured data is a type of data that combines features of both structured and unstructured data. It is data that does not conform to a fixed or rigid schema, but still contains some level of organization or structure. Semi-structured data does not follow the tabular structure of data models associated with relational databases or other forms of data tables, but it contains tags or other markers to separate semantic elements and enforce hierarchies of records and fields within the data.
Semi-structured data is typically characterized by the use of metadata or tags that provide additional information about the data elements. Examples of semi-structured data include XML documents, HTML code, graphs and tables, e-mails, and delimited files. Semi-structured data provides more flexibility in terms of data storage and management, as it can accommodate data that does not fit into a strict, predefined schema. This makes it easier to incorporate new types of data into an existing database or data processing pipeline.
Overall, semi-structured data provides a number of advantages over traditional structured data, including greater flexibility, adaptability, and scalability.
