Data classification can be defined as the process of organizing your data into various categories, making it a whole lot easier to retrieve, and perhaps even sort and store for future needs.
A well-laid out data classification system makes it easier for people to find and retrieve essential information. This can be particularly useful for those interested in legal discovery, risk management, and compliance.
Written guidelines and procedures for data classification policies help to define which criteria and categories an organization should use to classify their data. Or they specify the responsibilities and roles of employees within an organization with respect to data stewardship.
Once data classification has been established, security standards specify the most appropriate handling methods for all storage standards and categories that define data lifecycle requirements need to be addressed.
What Are the Benefits of Data Classification?
The careful planning of data classification systems will make it easier to manipulate or track your data. Commonly cited benefits of data classification include:
- Integrity of Data: Systems that will focus on data integrity will require some more storage and the right channels for access and user permissions.
- Confidentiality: Classification systems that value confidentiality above all other features will usually focus on their security measures, including encryption and user permissions.
- Availability of Data: When integrity and security will not need to be perfected, it is easiest to make your data a lot more accessible to its users.
- Greater Transparency: Data classification makes it easier to view how your data is being used and where it is moving.
- Deliver Immediate Insights: It’s easier to understand both content and context related to the data such as file type, storage location, and the user or application evaluate the worth of a document.
Common Methods of Data Classification
Whatever you may have heard, not all types of data will need to be classified, and some are just better off destroyed. It is vital for organizations to start prioritizing which kinds of data will need to pass through classification or reclassification processes.
With that said, data professionals and scientists are used to creating frameworks within which they can organize their data. This is done by assigning metadata or other kinds of tags in the information. The tagging then allows software and machines to instantly sort out their data into different categories based on relative sensitivity to the business.
This allows the deployment of security solutions such as data loss prevention to protect confidential information, especially when it is accessed and moved within or outside an organization. Classification tags can further reinforce the data sensitivity of a document and are an integral component of various data protection standards such as the CUI.
Unauthorized disclosure of such information that falls within one of these protected categories of the company’s data classification system will likely be a breach of protocol. In fact, in some countries, this will be considered to be a serious crime. To enforce the proper protocols, your protected data will first need to be sorted based on its category of sensitivity.
Data classification can also be used to categorize your structured data further, however, it will be especially important if you want to get the most out of your unstructured data. This will maximize its usefulness within your organization.
The Various Types of Data Classification
If you know a thing or two about computer programming, you may have heard of file parsing. This process involves splitting data packets into sets of smaller sub-packets, which makes them easier to move, categorize, or manipulate in any way you are comfortable with.
There are various parsing styles out there, and each will determine a different kind of information as input. For instance, the dates of your data may be split up by year, month, or day and all of the words may even get separated by spaces.
Four Types of Data Classification:
- Public Data: This information can be freely accessed by anyone with no restrictions and regulations monitoring its usage.
- Internal Data: This is internal information that should be kept within the company’s networks. Examples of this data include employee handbook, memos, and policies. The unauthorized disclosure of this information is of little consequence to the business.
- Confidential Data: This is confined within a specified business unit of a company. Information of this type includes marketing materials, pricing, contact information, and operational procedures. The disclosure of this data can negatively affect the business and its brand.
- Restricted Data: This information is strictly confidential and is kept on a need-to-know basis. Some businesses may protect the information with Non-disclosure Agreements (NDAs) to minimize their liability. Data of this type often relates to trade secrets credit cards, and personally identifiable information. Disclosure of this data could lead to significant financial and legal damage to a business.
Organizations may use different nomenclatures to establish a data treating method. The two widely used models for data treatment are as follows:
Sensitivity | Data Treatment Method 1 | Data Treatment Method 2 |
High | Restricted | Confidential |
Medium | Secret | For Internal Use Only |
Low | Public | Non-confidential |
As noted in the above table, many organizations prefer to use similar data treatment methods for both Confidential and Restricted Data to minimize their liability.
The Risks of Not Implementing Data Classification
Organizations that do not apply data classification schemes have a higher risk of data breaches with severe financial and legal consequences. More importantly, if an organization doesn’t properly classify its data, then it cannot properly enforce the policies for data protection.
It is worth mentioning that the weakest link in any data classification scheme is its employees. Even diligent employees can make mistakes when they do not have the time or incentive to classify data correctly. This is why many businesses prefer to use automated data classification systems to improve both accessibility and security.
Final Words
If you need assistance with any or all of these cybersecurity or data classification measures, Microsys is there to help. With us, you don’t have to worry about your budget constraints for cybersecurity and data protection. We offer solutions that don’t break the bank of small and medium-sized enterprises.
Please call (844) 406-0444 to talk with us. You can also send a message to info@microsysinc.ca.
