Data classification is a critical part of many company’s strategy for protecting data. In this post, we will look at data classification in terms of its purpose, types, and steps for the implementation of this process.

Common Purposes

The main reason for data classification is to ensure confidentiality. Many data systems have personally identifiable information such as credit cards, social security numbers, and more. Such information needs to be protected and the only way to know it needs to be protected is through classifying it as something that must be shielded.

Availability is another reason for data classification. Through classifying data, it helps a data governance team to know who should have access to what kinds of data. For example, the manager may have full access to all data while the assistant may only have access to data that is not considered confidential. Classification helps in determining access to data.

Data integrity is yet another reason. By ensuring that the data represent what it claims to be assessing what the data stands for. If data is classified as sensitive but does not contain any sensitive information it indicates a problem.

Data Types

There are also several different ways data can be classified. Data can be public which is generally not protected as it is accessible to all for the most part. Data can also be personal which is data that can be used to identify individuals and is usually strictly protected. Data can also be classified as sensitive which means data that requires access authorization.

Lastly, there is confidential information which is data that may have legal restrictions associated with it. The examples above are common forms of data classification. Individual organizations may use all or some of these classifications. In addition, there is nothing to stop an organization from creating its own distinct categories.

Steps

The process of classifying data is rather simple. First, you need to gather all the information that is needed to classify data. Part of this process is supported by having a data catalog that provides information on the location, owners, and content of the data asset.

Once it is clear what data is going to be classified, step two involves the development of a framework. This framework provides the structure for determining how to classify the data. The team involved in this process must develop the criteria for determining which category to place data in. When the categories are developed the data will be tagged. Once this is down the process can be automated using software.

Step three involves making sure the rules developed in step 2 are consistent with the standards that have been developed in the data governance policy. In other words, the classification must not violate the data governance policy because of compliance issues. There must be administrative consistency between data classification rules and the data governance policy

Step 4 involves the application of the rules developed in Step 2. Once this is completed the data classification is over at that moment.

Conclusion

Data classification is another tool that can be used to support an organization. This tool in particular is useful in protecting data based on its characteristics. Therefore, when it’s time to protect data a data classification can help you to determine what data to protect.