What is data classification? An overview and best practice

What is Data Classification?

Imagine going to a library where none of the books are organized — not by the Dewey Decimal System and not by genre. It would be difficult for anyone to find what they are looking for. The same applies to data, which is why any business collecting information should have data classification tools. But what exactly is data classification and why is it necessary for handling personally identifiable information (PII)?

Data classification is the process of categorizing data into relevant subgroups so that it is easier to find, retrieve, and use. It often involves marking or tagging data with a classification label such as “Confidential” or “Public” and simultaneously removing stale and duplicate data. 

Why is Data Classification necessary?

There are a number of reasons to conduct ongoing data classification, including maintaining compliance with ever-changing data regulations — like GDPR or HIPAA — and preventing security incidents.

Classification also acts as a visual cue for your employees and users to better understand the level of safety and alertness required when handling a given document. Knowing and using different types of data classification gives your business insight into the data it is creating, the data it is collecting and its level of sensitivity.

Data classification can also help you reach your business objectives and enhance operational efficiency. Knowing where millions of files are and what purpose they serve allows your company to analyze data and see trends, which enhances decision-making and streamlines productivity. Organizing data and identifying those trends early on can also reduce maintenance and storage costs.

How Data Classification works

Before you can classify data, you need to identify and collect it. Here are the three most common ways vendors organize the initial data before deciding how it should be classified.

1. Content-based classification

This approach involves looking at files directly and organizing them based on the kind of content and its level of sensitivity.

2. Context-based classification

This approach is efficient for classifying a lot of data from the same source as it examines metadata rather than the specific content. Parameters may include: 

• The application used to create the file or the file type (.xlsx or .docx) 
• The user/organization who created the file 
• The physical location of where data was created

3. User-based classification

A manual form of organization that sees a person or team decide how to classify individual files or data. User-based classification is reliant on personal discretion and the employee’s knowledge of what falls under sensitive data.

Types of Data Classification 

Generally, the more data classification labels you implement, the better you can manage your files and data. Most organizations use four classification labels ranging from information available to the public to PII and other sensitive data that could prompt legal action if not properly maintained.

Public data

This category of data is freely accessible to the public including all company employees. It can be freely used, reused, and redistributed without repercussions. An example might be marketing brochures, press releases, or a publicly- traded company’s stock report.

Internal-only data

This category of data is only available to internal personnel or employees who are granted access. This might include internal-only emails and correspondence, recordings or other communications, business plans, org charts, internal staff contact list etc. 

Confidential data (including PII data)

Access to confidential data requires special access privileges that must be strictly controlled. Types of confidential data can include sensitive personal information of customers and employees, M&A documents, privileged information protected under NDA, and more. Usually, confidential data is protected by data privacy and security regulation laws like HIPAA, GDPR, CPRA and the PCI DSS.

Restricted data 

Restricted data is that which, if compromised or accessed without authorization, could lead to criminal charges and massive legal fines or cause irreparable damage to the company. Examples of restricted data might include proprietary information or research and data protected by state and federal regulations.

What is the Data Classification process?

When done manually, data classification can be a tedious and complex process. Manual classification processes are vulnerable to human subjectivity compared to trained algorithms that a classification tool would rely on. However, humans should still be part of the process. While automation does streamline the overall process, you will still need processes and procedures in place that outline the roles and responsibilities of employees in your organization in regard to data classification.

Below are some basic steps to take when developing a data classification process.

1. Understand compliance requirements
2. Determine what information you are collecting
3. Establish processes and documentation for managing data
4. Identify how collecting this data will affect business objectives
5. Create documentation explaining how data levels will be assigned
6. Train employees on how to handle sensitive data using documentation
7. Scan and identify information using a data classification tool
8. Organize and classify results based on data sensitivity
9. Assign systems to manage unused data in compliance with regulations
10. Review processes to ensure ongoing classification and compliance

Classify data with Ground Labs

In order to properly classify data, you will need a data discovery tool. Not only will it help you have a complete understanding of where all your data resides and what category it belongs to, but it will assist your company in ensuring compliance with data protection laws. Our solutions, like Enterprise Recon and Card Recon, help businesses discover over 300 types of data across a variety of surfaces, such as desktops, email, and cloud, among other environments. These tools also help to remediate data compliance issues and keep your business functioning more efficiently. 

If you are ready to take control of your data and streamline your classification process with tools that also support compliance initiatives, contact us today.