Exploring data

Data refers to a set of values of qualitative or quantitative variables.

Data can be broadly categorized into three types:

• Structured data
• Unstructured data
• Semi-structured data

Structured data is data that we conventionally capture in a business application in the form of data residing in a relational database (relational database management system (RDBMS)) or non-relational database (NoSQL - originally referred to as non SQL).

Structured data can again be broadly categorized into two, namely raw and cleansed data. Data that is taken in as it is, without much cleansing or filtering, is called raw data. Data that is taken in with a lot of cleansing and filtering, catering to a particular analysis by business users, is called cleansed data.

All the other data, which doesn’t fall in the category of structured, can be called unstructured data. Data collected in the form of videos, images, and so on are examples of unstructured data.

There is a third category called semi-structured data, which has come into existence because of the Internet and is becoming more and more predominant with the evolution of social sites. The Wikipedia definition of semi-structured data is as follows:

Some of the examples of semi-structured data are the well-known data formats, namely JavaScript Object Notation (JSON) and Extensible Markup Language (XML).

The following figure (Figure 01) covers whatever we discussed on different types of data, in a pictorial fashion. Please don't get confused by seeing spreadsheets and text files in the structured section. This is because the data presented in the following figure is in the form of a record, which, indeed, qualifies it to be structured data:

Figure 01: Types of Data