Guide: Data Classification

Data Classification Software: The Best Data Classification Tools and Practices

Today, companies from all industries are generating, storing, and managing an unprecedented volume of data, particularly sensitive customer data.

With so many data types to manage, it’s more important than ever to ensure data is confidential, safe, and compliant. In order to achieve this goal, one of the most important activities companies need to adopt is a solid data classification strategy. This is typically accomplished using data or file classification tools, which can be free or paid.¬†

By reducing redundancies and partitioning datasets according to risk, sensitivity, and vulnerability, the right data classification tools can assist in properly categorizing, protecting, and reducing data.

This article will discuss everything you need to know about data classification for data security, particularly:

What is Data Classification Software?

Automated data classification assigns labels to information based on its category, level of sensitivity, and potential impact of data loss. Data classification informs companies about the importance of their data, identifying potential threats to that data, and putting safeguards in place to deal with those threats.

In this context, data classification software aids a company in meeting the following industry-specific compliance requirements:

Ultimately, if you are aware of the sensitive data you own, where it is located, and how it is used, you will better understand the best classification controls.

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Data Sensitivity Levels

For a seamless data management and risk assessment initiative, it is important to classify data according to its sensitivity level:

 

  • High Sensitivity Data: Exposure to this type of data would have an explosive effect on the organization or individuals if it were to become compromised or destroyed due to an unlawful transaction. Some examples include, records of financial transactions, intellectual property, and authentication data are some examples.
  • Medium Sensitivity Data: Designed only for usage within the company, yet even if it were to become compromised or destroyed, it would not have a devastating effect on the company or its employees. For instance, emails and papers that do not include any sensitive information.
  • Low Sensitivity Data: It is designated for usage by the general population. Take, for instance, the content of publicly accessible websites.

Types of Data Classification

It is possible to classify data according to content, context, or user preferences:

 

  • Content-based Classification: entails all content such as going through, filing and classifying paperwork.
  • Context-based Classification: includes organizing files according to metadata such as the program you used to produce the file, the name of the person who wrote the document, or the physical location of creation or where it was edited.
  • User-based Classification: involves assigning categories to files based on the manual decisions of a user experience in the field. People who work with documents can designate whether or not the documents are treated as confidential. This classification is made when the document is first created, following a significant modification or review, or just before the document is made public.

Examples of Data Classification Software

Data classification uses various tools, such as databases, business intelligence (BI) software, and conventional data management systems. These tools help streamline the data classification process.

 

Essentially, data classification tools pull data that meets certain criteria swiftly. This speeds up the entire data classification process allowing you to dictate classification criteria for the tool to use for classification purposes.

6 Data Classification Software Best Practices

To better classify data in your company, follow these six best practices for using data classification software:

1. Create Distinct Goals

Indicate what you expect to happen as a result of data classification. Classification typically occurs after data discovery. So, it is important to think about why you want to conduct data discovery in the first place. Data classification’s primary goal is to locate and label sensitive information across all data stores so you can implement security policies effectively.

2. Define Labels for Use in File Types Tagging

You may determine the importance and potential implications of a data breach with the help of a data classification tool. This also helps you determine the sensitive nature of the data in question.

 

It is common practice to identify information as either “public,” “private,” “internal,” or “restricted” in descending order of accessibility. These tags ensure appropriate data security measures by assigning unique identifiers to each data set.

3. Synchronize with Data Discovery

Synchronizing categorization policies with discovery policies aids the development of data security measures. If data discovery and categorization systems are deployed separately, it is crucial to combine them seamlessly. You can also assure content-aware protection by combining both tools into a unified data risk assessment solution.

4. Comply with the Standards

HIPAA, PCI DSS, GDPR, and other regulations make data classification mandatory. It is essential to carefully assess the compliance needs to discover the data dangers and the data management rules. Therefore, verify that all procedures dealing with private information adhere to the mandated security standards.

5. Conduct Testing and Validation Processes

Data sorting and file tagging should be piloted on a smaller scale before applying it to a large dataset. Procedures can be compared and modified to better suit the needs of the business, achieve desired outcomes, and fulfill regulatory and compliance mandates.

6. Institute Regular Reviews

Due to data expansion, strict compliance requirements, new data threats, and shifting business needs, it is important to regularly update the data classification process to guarantee data security.

 

To incorporate updates more smoothly, leave some flexibility in your data classification plan.

Conclusion

The use of data classification tools aids businesses in protecting sensitive information while also making it easily accessible and ensuring its integrity.

 

Today, companies rely on a data classification policy as the bedrock of their data security practices. After all, providing sufficient security for private information is hard if it isn’t properly classified. Satori automatically detects and classifies sensitive data without requiring additional configuration. This ensures that your data inventories are always up to date, regardless of whether you have standard or custom data.¬†

 

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Last updated on

October 12, 2022

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