Nowadays, the digital world is increasing, and information is everywhere. But, what exactly are the three types of data? We can define it as a collection of information, about quantities, characters or symbols on which perform the operations. Then, it can be in the form of numbers, text, videos or images. We classify them in three types of data in order to differentiate them and to treat them. This information can come from different sources, such as social media posts, or scientific experiments. In this article, we will present you the three types of data and their characteristics.
The structured data:
Firstly, in these three types of data, we have the structured data. It is stored and processed in a fixed and well-defined format. Then, it is organized in a systematic and predictable way, making it easier to consult, analyze and use.
Moreover, we generally stock the structured data in databases, and then follow a strict organization that defines the data types, fields, and relationships among the different entities. They can be numerical or textual.
Structured data could be for instance Excel spreadsheets, CSV files, database tables, etc. From the three types of data, this one is ideal in the financial area, in healthcare or electrical trading.
Three types of data: Example of structured data:
| ID_Client | Last Name | First Name | Birth Date | |
|---|---|---|---|---|
| 1 | Smith | Maria | maria.smith@6.com | 1993-01-25 |
| 2 | Dupont | Jean | jean.dupont@1.com | 1985-06-12 |
Thanks to the advances that have been made in the field of information technology, there are now techniques that make it possible to work efficiently with this kind of data and extract all its value.
Despite that, structured data presents some challenges, as it has a big volume. Indeed, as it can reach zettabytes, processing and managing this data can be difficult.
The semi structured data
Semi-structured data has the distinctive feature of having a partial structure which, unlike structured data, does not strictly follow the format of relational databases. Consequently, human users can manage it easily.
It contains contextual elements such as tags, labels, metadata or tags that make them simpler to organize, process and manipulate than unstructured data, while being less rigid than structured data.
For example, text files, images or contact lists are good examples of semi-structured data. However, the manipulation of such data requires the use of the XML language, which allows to annotate the information without imposing a rigid schema.
The unstructured data
Finally, the unstructured data. It contains information that does not follow a defined format or strict organization. Unlike structured data, which we store in databases with a well-defined structure, unstructured data is the more flexible and varied of the three types of data. Then, an important feature of unstructured data is the diversity of the formats existing.
This is because information can take many different forms, such as text, images, videos, audio recordings, emails, presentations, PDFs and so on. This variety makes it possible to capture rich, contextual information. Human users often generate it without any specific constraints. Consequently, this type of data contains contextual details, emotions and nuances, making them essential to the overall understanding of a text, image or video. Unstructured data also presents a number of challenges in terms of processing and exploitation, over and above its massive volume.
A good example of unstructured data is a heterogeneous data source containing a combination of text, image and video files, or social media feeds. In this current digital and multimedia age, this type of data is increasingly common. Companies therefore have vast quantities of data at their fingertips, but are struggling to make the most of it because of the difficulty that represents the processing of this unstructured information.
Do you have further questions? Click here to contact us.
2 Responses