When they are not administered, the data can become overwhelming, which makes it difficult to obtain the information that is needed at the time. Fortunately, we have software tools that, although designed to address data storage effectively, discovery, compliance, etc., have as a general objective to make the management and maintenance of data easy.
What is structured data?
When we talk about structured data, we refer to the information usually found in most databases. They are text files usually displayed in rows and columns with titles. They are data that can be easily ordered and processed by all data mining tools. We could see it as if it were a perfectly organized filing cabinet where everything can get identified, labeled and easily accessible.
It is likely that most organizations are familiar with this type of data and are already using it effectively, so let’s move on to see the unstructured data.
What is unstructured data?
Although it seems incredible, the database with structured information of a company does not even contain half of the information that is available in the company ready to be used. 80% of the information relevant to a business originates in an unstructured form, mainly in text format.
Unstructured data is usually binary data that has no identifiable internal structure. It is a massive and disorganized conglomerate of several objects that have no value until identified and stored in an organized manner.
Once organized, the elements that make up their content can be searched and categorized (at least to some extent) to obtain information.
For example, although most data mining tools are not capable of analyzing the information contained in email messages (however organized they may be), it is possible that collecting and classifying the data contained in them can show us relevant information for our organization. It is an example that illustrates the importance and scope of unstructured data.
But e-mail has no structure?
The unstructured term faces different opinions for various reasons. Some people say that although a formal structure cannot get identified in them, it is possible that it could be implicit and, in that case, it should not get categorized as unstructured. However, on the other hand, if the data have some form of structure, but this is not useful and can not be used to process them, they should be categorized as unstructured.
Although e-mail messages may contain information with some implicit structure, it is logical to think of them as unstructured information, since common data mining tools are not prepared to process and analyze them.
Unstructured data types
Unstructured data is raw and unorganized data. Ideally, all this information could be converted into structured data. However, it would be somewhat expensive and would require a lot of time. In addition, not all types of unstructured data can easily be converted into a structured model. For example, following the e-mail example, an e-mail contains information such as the time of sending, the person to whom it is sent, the sender, etc. However, the content of the message is not easily divided or categorized and this can be a problem of compatibility with the structure of a relational database system.
This is a limited list of unstructured data types:
- Emails.
- Text processor files.
- PDF files.
- Spreadsheets.
- Digital images
- Video.
- Audio.
- Publications in social media.
Looking at that list, you could ask what these files have in common. These are files that can be stored and managed without the system having to understand the format of the data. Since the content of these files does not get organized, they can get stored in an unstructured way.
Precisely many qualified voices in the sector suggest that it is unstructured information that offers greater knowledge. In any case, the analysis of data of different types is essential to improve both productivity and decision making in any company.
The Big Data industry continues to grow, but there is a problem with unstructured data that do not get used yet. However, the companies have already identified the problem and technologies and services are already being developed to help solve it.
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