What is Data Classification?
Data classification is a data management process whereby organizations categorize various information assets based on the sensitivity of the document’s contents and the audiences who should have access to said documents . These organizations might apply security policies to facilitate this process.
An important part of the information management lifecycle, data classification lets organizations access and share information quickly and securely. Proper categorization also improves compliance and helps organizations adhere to GDPR, HIPAA, FERPA, and other data protection regulations.
Data classification is important because it allows organizations to manage their data more effectively and accurately. These organizations might have information assets spread across different channels (network or cloud applications) or locations (network servers, folders, and hard drives), which makes information visibility and access difficult. Data classification solutions help organizations quickly identify where sensitive data resides, facilitates proper labeling of this critical data and protects how this information is accessed and/or shared.
Organizations who classify data also improve security credentials because they can better manage sensitive and valuable information . Data classification, therefore, could reduce the likelihood of a data breach or other type of cyberattack.
Data Classification Methods
Organizations use various methods to categorize data. These include identity access management, data encryption, data forensics, and automation .
Identity access management (IAM)
Organizations can limit access to data to those who don't have permission rights. Employees will only be able to access information assets with a password, for example.
Organizations can encrypt sensitive information assets in order to prevent third parties from accessing this data.
Automation is delivered by enabling policies in a data loss prevention (DLP) solution to identify, detect and apply data labels, when combined with a data classification solution. This solution, available with Forcepoint DLP, can help to balance user-driven classification with automation to streamline data classification, reduce user error and improve overall security awareness.
Types and Examples of Data Classification
Typically, a Chief Information Officer (CIO) or Chief Information and Security Officer (CISO) is the person responsible for data classification within an organization. A CIO or CISO will liaise with different departments —management, HR, sales, finance, etc. — and ensure information assets are safe, accessible, and adhere to local and federal legislation and regulations. While there may be a data classification lead, organizations should involve key stakeholders across the entire organization . This will enable organizations to more effectively adopt data classification processes.
Data classification might require an initial outlay, but it could provide organizations with a return on their investment. Information officers might need to migrate data from hard drives to the cloud, for example, in order to improve security, accessibility, and compliance. However, good data classification tools could save organizations from expensive penalties for non-compliance.
In the healthcare sector, the federal government can impose penalties from $100- $50,000 on organizations for data protection violations, with a maximum penalty of $1.5 million per year for repeat violations .
Keep in mind, data classification is an ongoing process that will require fine tuning and process modifications as user engagement with data and data sensitivity changes over time.
Data Classification Best Practices
For more effective data classification, organizations should take the following steps:
- Identify where critical IP or regulated data resides — This could include hard drives, databases, network files, folders, cloud applications, etc.
- Define data categories – Keep it simple by avoiding complicated or exhaustive classification schemas 
- Detect the most valuable data and leverage technology, such as data classification and labeling automation tools, to safeguard this sensitive information.
- Train existing and new employees how to handle sensitive data, including providing tools and resources for ongoing security awareness.
- Adhere to local, state, and federal data protection legislation and regulations and understand the penalties for non-compliance.
- Build a data classification strategy that empowers users to contribute to and take responsibility for properly handling critical IP or regulated data within an organization.