Classifying data can serve numerous purposes and have countless benefits for professionals. There are also many naming conventions that you can follow to classify data. Below, the article will break down some of the basics of data classification, and also shed light on its importance.
What is data classification?
Data Classification refers to the process in which you organize structured and unstructured data. You have to organize them into exclusive categories that will be based on different types and content. It is worth noting that these exclusive classes or categories are usually part of a hierarchy. Most often, data comes under classification due to its sensitivity.
Data also undergoes classification based on the type of data and the contents which it contains. You can also classify data into particular levels, groups or classes. There are many different levels of classification. Without levels, you cannot implement the hierarchy that is needed to classify data. The most common levels of information classification are Public, Sensitive, and Confidential.
This level of classification is extremely high risk and requires stringent access controls and sophisticated protection mechanisms. Oftentimes, data that is classified into the confidential level includes government intervention for protection.
Government organizations such as GDPR, CCPA, HIPAA and others are acting bodies when it comes to protecting confidential data. One of the primary reasons why government organizations are at work for this type of data is because any breach of them can cause significant harm to government organizations.
Data that falls into the sensitive category is medium risk. This data is only for internal use. However, the consequences of the data breach are not disastrous. An example of sensitive data would be a strategy document, or employee data. It can also be a financial statement as that is not something people are comfortable sharing, but there is no real harm even if they do.
This level of data is low risk data. It refers to information that does not require any access restrictions. Examples of this type of data include any information that you come across on public web pages. It also pertains to job postings and business contact information.
Despite the three main classifications, it is worth noting that you can have as many classifications as your want. For instance, the US government has seven classifications for their data. They involve, restricted, code word classified, top-secret, secret, confidential, public, and controlled unclassified.
The names for these classifications of data can be strange. However, since the US government handles a wide variety of information, the data can easily fall into some of those categories. Restricted data is concerned with nuclear information. This type of information stays classified and you cannot declassify it.
Code word classifications involve data that is top secret and requires codeword clearance administered by the CIA. Top secret is another classified data that is mostly in the possession of security forces such as the CIA. It contains information that they cannot afford to disclose unauthorized. If it happens to get exposed, national security will have to suffer grave damages.
As you keep going down the classifications such as confidential, public trust, and controlled, the restrictions towards their privacy start to become less stringent. They have a lesser chance of causing significant damage if they were to get out.
Importance of Data Classification
Data classification categorizes data according to its sensitivity level. In other words, when you classify data, you put it under classifications that are either high risk, low risk, or medium risk. According to the risk associated with their breach, you can set up classes according to different nomenclatures. You can also have multiple categories and are not limited to only three.
You may then ask why data classification is so important. One of the more obvious reasons why data classification is important has to do with privacy. However, there is more to data classifications than just privacy. There are four main uses of data classification. These include risk mitigation, efficiency, analytics, and compliance.
If you take into account risk mitigation, classifying data allows people to limit access for important data. By classifying data, one can ensure that only limited employees have access to particular data. On the other hand, governance and compliance include adding regulations to specific data. This way, managing data becomes standardized and efficient.
As you can see, classifying data is an act that serves multiple purposes apart from privacy. Some prefer to optimize the data, while others like to perform analytics using the classification method.