Types of data
You might have appeared for n number of examinations; both the objective and subjective type. Before the exam, the model paper or the format of the examination will be published. The exam paper format will be according to that only. But it is not the case when you attend an interview. The person sitting in front of you might ask any question. For example, the most common question, “tell me about yourself”. The questions that have to be asked don’t follow any structure or model. Also, when an HR takes the interview, that could be based on a script or could be random or both. So, with this note, we shall start with our discussion: different types of data.
There are three types of data: Structured, Semi-structured, and Unstructured. We shall now discuss each of them.
Structured Data:
The information that is collected, formatted, and filled into a pre-defined data model is known as structured data. The raw data is filled into the pre-defined fields and is later extracted and read easily. SQL is an example of structured data as the raw data is fed to the rows and columns of the table that is well-defined earlier.
For example, every one of us has used excel to fill the school data, passwords (not recommended), etc. Excel is a perfect example of structured data. The analogy of examination that is aforementioned is also an example of structured data. The structured data is most processed in the development and simplest way to manage information.
Semi-structured data:
We have discussed the hybrid interview: both based on the model paper and random questions. This explains the concept of semi-structured data. It doesn’t reside in the relational database as the structured data but it has some organizational properties (consistent and defined properties) that make it easier to analyze.
Example:
The delimited files are examples of semi-structured data. A delimited file is a method of representing the data of a table in a text file using characters to represent the rows and columns. The examples of delimiter files are CSV (Comma-Separated Values), TSV (Tab-Separated Values), PSV (Pipe-Separated Values), etc. The XML file format is also an example of semi-structured data.
Unstructured Data:
The random question, “tell me about yourself”, could be an example of unstructured data. The absolute raw format of the data is unstructured. This type of data, unlike the remaining, doesn’t have any pre-defined data model or order. It is not easy to process and analyze unstructured data.
Examples of unstructured data include word files, log files, emails, etc. An example for the analysis of unstructured data is analyzing emails for spam or phishing emails.
Structured Vs Semi-structured Vs Unstructured:
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