Semi structured data contains both structured and unstructured data or structured semi-structured and unstructured data. This data has structure but is not the same as the data model’s structure and lacks the rigid/fixed schema with types of data structured unstructured semi-structured. The fact that such does not reside in the rational database due to its organisational properties makes its analysis easier. At times such data can also be stored in a relational database.
As said above, semi structured data lacks a fixed schema. It has the below characteristics.
Semi structured data is obtained from varying sources. Some of the types of semi structured data are
Working with semi-structured data has its own advantages. Some of them are
With advantages come disadvantages too. Some disadvantages and difference between structured and semi structured data are
 Since heterogeneous sources are used, semi-structured data generally have only partial structure or no structure at all. Thus to index or tag the data and information extraction from semi-structured data is a tough job. These issues can be solved as follows.
It is critical in information extraction and data analytics to understand the differences between structured, semi-structured data and unstructured data. Understanding the data also enables more accessible storage of such data and zeroes in on the various techniques used to extract, search, find and analyse such data.
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