What should your data classification strategy consist of?

A data classification strategy or policy is essential if your organization handles sensitive data like intellectual property, Personal Identifiable Information (PII), or any additional information subject to compliance regulations. Unfortunately, many organizations find it difficult to adequately protect data under their control. The solution to this problem is to enact a proper data classification strategy that provides comprehensive coverage of your threat surface, adequately monitors data under your control, and offers clear procedures in the event of a security breach.

What is data classification?

Data classification is the overarching idea used to describe the process of separating and organizing company data based on a given set of characteristics, such as the sensitivity level of information, potential risk, or a given set of regulations that must be followed. This information can exist on your company servers, in the cloud, or on countless other systems and devices, further complicating the organizational process. Classifying data gives an organization insight into what can otherwise be a chaotic collection of improperly secured data of all types.

What is a data classification strategy?

A data classification strategy gives your team a shared playbook for protecting organizational data. This strategy lays out clear guidelines for your team responsibilities as well as procedures to follow to create an effective data classification plan.

While nearly all businesses can benefit from some form of data classification strategy, organizations that collect a large amount of sensitive data or are subject to significant regulations should see a data classification plan as an essential part of doing business. Financial institutions, healthcare facilities, and all companies dealing with payment card information fall into this category.

How to set up a data classification strategy for your organization

Every organization’s data classification policy will vary based on need. However, all policies can be simplified to three key areas. Use these steps as a starting point when creating your data classification checklist.

Step 1: Know your threat surface

Data discovery is essential to the data classification process. To protect your data, you must first have a clear understanding of what kind of data you have and where it lives. Accurate data discovery, particularly automated semantic data discovery, provides several key benefits in regards to your data management:

  • Increased transparency. Your organization will have a better picture of data held on your systems. With this information, you can react more quickly in the event of a breach.
  • More efficiency. With proper data discovery, your organization can leverage all data at your disposal and fill in blind spots resulting from dark data.
  • Improved security. With a complete picture of your organization’s data, your team can reduce risks resulting from unstructured data and improper permissions.

Data risk assessments

A data risk assessment is a key part of the initial data discovery process and can give you greater insight into your organization’s sensitive data. When you perform a data risk assessment, your security team will be able to better identify the volume and vulnerability of the information under your control.

Step 2: Properly monitor your data

Knowing where your data lives isn’t enough to protect it properly. Your organization needs a sensitive data watcher in order to take a proactive rather than a reactive approach to data security. Once data is secured and classified, predefined rules need to be in place to ensure only intended and authorized users can access information on your system.

Common data classification matrix guidelines

While your organization may require more specialized classification guidelines, the most basic data classification schema includes four main classifications based on the sensitivity of the information being organized:

  • Public. Public data is already available on public networks and is not considered to be sensitive.
  • Internal. Internal data is for internal team members only and is not intended for wider distribution to the general public.
  • Confidential. Confidential data belongs to a company or its customers. As a result, this information can cause reputational or financial harm to your company if not properly protected.
  • Sensitive. Sensitive data is data subject to regulatory oversight. This data can cause significant harm to consumers and your organization in the event of a breach or data leak.

Step 3: Establish contingency plans for security events

Data breaches can occur even with a security plan in place. Your organization needs to have a plan in place to mitigate and remediate any damage incurred as a result of the breach. The risks of data breach noncompliance include financial penalties and reputational backlash that can harm your organization for years to come, further underscoring the importance of a proper data classification strategy that allows for rapid and effective detection and containment.

Improve your data classification procedures

To protect your organization from data breaches, regulatory noncompliance, and other organizational threats, you need a powerful tool capable of delivering cutting-edge data discovery, classification, and remediation. The Spirion Sensitive Data Platform delivers precisely this, with 98% accuracy and 15 years of industry-leading experience.

Find your sensitive data where it lives, track it with unmatched accuracy, and understand your data at a level not previously possible. Contact us today for more information or schedule a demo to see our products in action.