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Data, in today’s digital age, is extremely valuable. In fact, it’s no secret that businesses, organizations, and individuals rely heavily on data to make informed decisions and operate efficiently.
But with the vast amount of data being generated every day, it’s becoming increasingly difficult to identify and classify it properly.
Data classification is a critical step in cloud security posture management for protecting your sensitive information from cyber threats, data breaches, and other security risks.
It involves identifying the type of data you have, categorizing it based on its sensitivity and value, and determining the appropriate security measures to protect it.
Proper data classification is essential for maintaining compliance with data protection laws and regulations, such as the General Data Protection Regulation (GDPR) and the Health Insurance Portability and Accountability Act (HIPAA).
Failure to classify data correctly can result in hefty fines, legal action, and damage to an organization’s reputation.
In this article, we’ll explore the various types of data classification along with its process and steps to select a solution for identifying and classifying your data for better security.
Understanding Data Classification
Depending on the scale and scope of your business, you could be dealing with large volumes of data. You are going to need a good mechanism for classifying all the data and ensuring that it is easily accessible and organized.
Data classification is generally defined as the process of organizing structured and unstructured data into concrete categories that separate different types of data.
To understand it more deeply, you could say that data classification will help you categorize data based on its type, sensitivity, and its value to your business. With the help of data classification, you will need to assess whether data is at risk and have mechanisms to mitigate those risks.
We will now look at the various levels of sensitivity that you should consider while classifying any kind of date. These are:
- High-sensitivity data: This type of data is highly valuable to organizations and could have a catastrophic impact on them in case such valuable data is compromised or destroyed.
Type: Authentication Data, Intellectual Property, Financial Records
- Medium sensitivity data: This type of data is generally made accessible only to internal stakeholders or authorized personnel. While the loss of such data may not have a catastrophic impact on the organization, it is still to be kept.
Type: Messages or documents that include confidential data
- Non-sensitivity data: Does not contain any confidential data and is intended for public use.
Type: Website content, blogs, public resources
Purpose of Data Classification
Before you blindly go about classifying your data for security reasons, you may want to understand the purpose behind doing so. Broadly speaking, data classification can help organizations achieve regulatory compliance, and improve the security of their data.
Some of the main purposes behind data classification are as follows:
- Helps organizations to make sure that the necessary security measures are implemented
- Improves the productivity and decision-making capabilities of the users
- Helps you create informed processes for risk management, regulatory compliance, and legal discovery
- Enables IT teams to justify investment requests for data security
With so many reasons associated with data classification, there is little doubt that you should be considering it to ensure data security.
Types of Data Classification
It is important to consider at this point that data classification can be carried out based on three parameters — context, content, and user specifications. Let us understand what each type of data classification entails.
- Content-Based Classification: This classification involves reviewing the contents of documents and files, and sorting them accordingly.
- Context-Based Classification: This classification entails sorting your files and data based on their metadata or specific common aspects. For instance, you may want to classify your data based on the software used to create it, the file type, or the location in which the data was authored.
- User-Based Classification: This classification entails having a knowledgeable user decide how the data should be classified. This classification generally done by the document owner can be done when it is created, or after it is edited and reviewed.
So, yes, you have quite a few decisions to make before you can embark on the process of data classification. Security experts suggest that you take an approach that is a combination of the above classification types so that you can get the best of human input, and efficiency of software tools.
The Data Classification Process
Once you assess the sensitivity level of your data, and choose a type of classification to go with, all you need to do is start classifying your data. While every individual is free to choose a process of their preference, coming up with the most effective data classification policy is complex and can feel overwhelming.
Before beginning to classify your data, it is essential that you backup your data properly, to avoid any kind of data loss and safeguarding critical data.
To ensure that you implement the most effective process in this regard, you can divide the process into four steps.
- Discovery: In this stage, you will identify all the sources of sensitive data in your business. The data can usually be found on laptops, desktop computers, and even on the cloud. Thus, the first step consists of diligent efforts targeted at finding and narrowing down the most sensitive data in your business.
- Classification: To protect your data effectively, the second stage will entail classifying and organizing your data. This will be the first step towards building a data security program, which can provide accurate protection to crucial data in your business.
- Policies: In the first couple of stages, you would have already gotten access to crucial and sensitive data. Since you would have also classified the data, you will now need to define how you plan to protect it. Setting down a protection policy for your sensitive and crucial data is the next step in the process.
- Enforcement: Provide alerts for any risky behavior so that users can go ahead and make corrections as required. You will need to implement data protection policies and ensure that they are followed till the very end.
Having this kind of predefined process, and classifying all your data effectively ensures that you can save it from any internal or external threats.
How to Select a Data Classification Solution?
Selecting the right data classification solution is not an easy feat. That’s why many organizations are turning to data classification solutions to automate the process and improve their data protection measures.
But with so many data classification solutions available on the market, it can be overwhelming to select the right one for your organization’s specific needs.
Fortunately for you, we’ve already explained a list of factors to consider when selecting a data classification solution.
Step 1. Identify Your Data Classification Needs
Before selecting a data classification solution, it’s important to identify your organization’s specific data classification needs. This involves understanding the types of data you have, the sensitivity of that data, and any regulatory compliance requirements you need to meet.
For example, if you’re a healthcare provider, you may need to classify patient data as highly sensitive and meet compliance requirements under HIPAA.
On the other hand, if you’re a financial institution, you may need to classify financial data as highly sensitive and meet compliance requirements under the Gramm-Leach-Bliley Act (GLBA).
Understanding your organization’s specific needs will help you determine the appropriate classification levels and security measures required.
Step 2. Determine the Level of Automation Required
Data classification solutions range from fully automated to manual solutions. If you have a small amount of data, a manual solution may suffice.
However, if you’re dealing with large volumes of data, an automated solution is more efficient and effective. Automated solutions use machine learning algorithms to identify and classify data based on predefined rules and criteria.
So, determine the level of automation required based on the size and complexity of your data.
Step 3. Evaluate the Accuracy of the Solution
The accuracy of the data classification solution is critical. A solution that generates too many false positives or negatives can be time-consuming and frustrating.
That’s why you need to ensure that the solution you select accurately identifies and classifies data based on your organization’s specific needs.
You can evaluate the accuracy of the solution by testing it with sample data and comparing the results to your organization’s classification requirements.
Step 4. Consider Integration with Other Solutions
Data classification solutions can integrate with other security solutions to create a comprehensive data protection program.
But, you must find out whether the solution you select can integrate with your existing security infrastructure, such as data loss prevention (DLP) and data encryption solutions.
Integration with other solutions is extremely vital because it can help to enhance the accuracy and effectiveness of your data protection measures.
Step 5. Evaluate the Vendor’s Reputation and Support
When selecting a data classification solution, consider the vendor’s reputation and support. Research the vendor’s track record, customer reviews, and technical support capabilities.
Ensure that the vendor has a good reputation and offers excellent technical support to help you implement and maintain the solution.
This is important because a vendor with a good reputation and strong support can provide added value and peace of mind.
Step 6. Consider the Solution’s Scalability
As your organization grows, so does your data. This is why it is critical to select a data classification solution that is scalable and can grow with your organization’s data protection needs.
Ideally, you should look for each solution’s ability to add additional users, data sources, and classification levels as your organization evolves.
The right data classification solution can help you avoid the need to switch to a new solution as your organization’s data protection needs change.
Step 7. Evaluate the Solution’s User Interface and Ease of Use
Finally, consider the data classification solution’s user interface and ease of use.
Ensure that the solution has an intuitive user interface and is easy to use, even for non-technical users. This will help ensure that the solution is effectively adopted and used throughout your organization.
Simply put, it is recommended to go with a user-friendly solution that can help streamline the data classification process and enhance data protection measures.
Classify Data Effectively for Better Security (Conclusion)
As you have just learned, selecting a data classification solution requires careful consideration of your organization’s specific needs. But, by following the steps outlined in this article, you can identify the appropriate solution that meets your organization’s data protection needs and regulatory compliance requirements.
Remember, data classification is an ongoing process that requires regular review and updates as your organization’s data evolves.
So, stay vigilant in your data protection efforts, and your organization will be better equipped to prevent data breaches and maintain the trust of your customers and stakeholders.
Are you ready to take your data security to the next level?
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At The Data Scientist we offer a wide range of data science courses designed to equip you with the expertise needed to identify, classify, and secure your data effectively. Our courses cover topics such as data classification techniques, data protection regulations, and the latest tools and technologies in the field.
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Don’t wait until a data breach occurs. Act now to safeguard your sensitive information and mitigate security risks. Visit TDS to explore our data science courses and learn more about our data science services. Empower yourself or your organization with the knowledge and expertise to protect what matters most – your valuable data.
”What is data loss prevention (DLP)?”. 2023: www.microsoft.com/en-us/security/business/security-101/what-is-data-loss-prevention-dlp
“Gramm-Leach-Bliley Act”. 2023: www.ftc.gov/business-guidance/privacy-security/gramm-leach-bliley-act