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Data Classification: Importance, Guidelines and Best Practices

February 14, 2021 • Data Security • 6 min read
Data-Classification-Importance-Guidelines-and-Best-Practices

Nobody wants their data, passwords, and accounts compromised, that is why data classification is highly critical to prevent the risk of cyber threats. Having an adept knowledge of information management helps you to strengthen security and deter ransomware attacks. Whether the data comes from a network, cloud application, or hard drives, access and visibility should be protected through data classification solutions.

What is Data Classification?

This is a standard step for companies that control a vast amount of sensitive data. Aside from reliable protection and strategy against a security breach, data classification is an effective approach in managing and identifying certain types of data.

The ability to organize sensitive and valuable information can improve the company’s security strategy. The procedure also helps eliminate unnecessary information assets while re-organizing data into distinct categories. It also helps the organization in determining who has access to certain data and how long it should be preserved.

Four classifications of data:

  • Public – All information that is accessible in the public domain can be used, reused, and redistributed by anyone. Examples of public data are first and last names, press releases, or job descriptions.
  • Confidential – Considered as private and identifiable data, the government and local state usually regulate this and categorize them into employee information, management information, and business information. Data under this category are social security numbers and other documents protected by laws.
  • Sensitive – Regarded as ethical or legal data, it requires top security to avoid unauthorized disclosure. It includes trade secrets, customer information, and other critical information within the business.
  • Personal – Any information used to identify an individual such as phone number, home address, appearance, and account data.

Ways to Classify Data

There are different ways to classify data, however, it depends on the industry to which you belong. When classifying data there are a few things you should consider which includes the following:

  • Identify what kind of data you need to collect from customers and traders.
  • Determine the data your organization needs to create.
  • Assess the data sensitivity levels – high, medium, or low. High levels have a detrimental impact on the company when used maliciously.
  • Restrict the data access to admin and specific employees only.

There are two primary methods to obtain data classification:

  1. Treat all data as restricted and add rules within your system that could help track and handle information accordingly using a certain application.
  2. Train your staff to have a better comprehension of a data sensitivity level and familiarize themselves with proper labeling and usage of these documents. It entails patience and perseverance to accomplish but proven effective because humans can identify data easier in various contexts.
Data-Classification-Importance-Guidelines-and-Best-Practices

Purpose of Classifying Information

To fully understand your stored data and its location, here are the main purpose and importance of data classification:

Risk Management and Regulatory Compliance processes

Executing an effective operational strategy regularly especially when searching and tracing data, organizations can control and eliminate any kinds of business risk.

Privacy

Now that you were able to manage risks, it’s time to determine the sensitivity and privacy of each asset through procedures in handling confidential information. Since there is no one-size-fits-all data protection strategy, technical controls and proper education are the best practices for privacy.

Security Measures

This is the main purpose of classifying data. When you are fully aware of data confidentiality, it will be much easier to know exactly how to secure your devices and networks. To avoid further outside threats, organizations may run the strongest firewall and follow the standard data protection.

Monitoring for insider threats should also be done regularly. Insider threat cases often involve data theft or data breaches due to employee negligence that’s why having trained individuals in your workforce can improve and mitigate such cases.

Best Practices for Data Classification

Here are the best practices that every organization should follow to manage data classification effectively:

1. Leverage technology to assess the most valuable data using labeling automation tools that require authentication from users before they could access confidential information and internal networks.

You can also deploy different tools essential for data management like Data Loss Prevention (DLP), Software as a Service (SaaS), and AI-driven security tools.

2. Understand the penalties and follow the policies of your local, state, and government for regulatory compliance. Have a regular assessment of your organization’s regulated data, update your technology, and adhere to the changes and modifications based on federal laws. Organizations must imply strict policies because ignorance of the law is not an exception for non-compliance.

3. Businesses should modify and build their reliable data classification strategy that encourages users to be more active and responsible in managing and protecting and managing critical data.

Need assistance in handling data properly? We are glad to help you assess risks and establish a data classification strategy for your company. Contact us today!

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