1. About Big Data

Big data refers to an enormous proportion of information data whose volume requires specific analysis methodologies and technologies for research purposes of any kind. The three fundamental characteristics of these information sets - the so-called three Vs - are:

• Volume. This is particularly voluminous data, implying that it is capable of taking up a lot of space, starting in the order of terabytes up to petabytes;
• Speed. Although the amount of data is particularly rich, it must be decoded and read in the shortest possible time. The determining factor for the handling and correct management of big data, therefore, is the speed.
• Variety. Big data are defined as unstructured or semi-structured data and this constitutes an additional difficulty, as preliminary analysis is required before they can be processed.

In even more recent times, other characteristics have been combined with the three Vs:

• Veracity: In order for Big Data to be processed properly, it must be filtered; as it is raw data, it can lead to incorrect analysis and a high risk of statistical error and interpretation.
• Value: Not all big data may have value depending on the purpose for which it is processed and interpreted. Again, those of interest should be selected before analysis.
• Variability: They can be filtered, categorised and used in different ways according to the useful purpose.

There are generally three types of data: structured, semi-structured and unstructured. It must be emphasised, however, that data and information are not synonymous because - especially in computer science - information does not exist per se, rather it is retrieved through the processing of collected data.

When we speak of structured data, we mean a type of information that can be easily encapsulated and organised into data fields since it is characterised by a precise structure; to give an example, we can think of a table similar to this one, containing three different columns containing fields:

When we speak of semi-structured data, we are referring to a type of information, part of which can be encapsulated in data fields - and is therefore structured data - while another section is made up of unstructured data; a case in point is that of e-mails, in which some fields are predefined, such as the sender, the addressee and the subject, while the body of the e-mail - i.e. the message we send - is in the form of unstructured data since it cannot be encapsulated in a specific field.

^{Figure 1 - Classification of data within an e-mail}

As far as big data is concerned, it takes the form of unstructured, semi-structured and structured data.