Data classification is a critical first step in safeguarding sensitive information, enabling organisations to identify, categorise, and protect data according to its level of sensitivity.

However, starting a data classification project can seem daunting, especially for businesses that are new to this practice. This guide will walk you through the essential steps to kickstart your data classification process effectively.

1. Understand the Importance of Data Classification

Before diving into the steps you’ll need to take, it's crucial to understand why data classification is necessary. Data classification helps businesses manage and protect their data more efficiently by categorising it based on its sensitivity, importance, and access needs.

Proper classification allows you to:

• Improve data security by applying appropriate protection measures.
• Ensure regulatory compliance with standards like GDPR, HIPAA, PCI DSS and CCPA.
• Enhance data management by enabling easier retrieval and use of information.
• Reduce the risk of data breaches and their associated costs.

With these benefits in mind, you’re better equipped to understand why a structured approach to data classification is essential.

2. Define Your Data Classification Objectives

Every data classification project should begin with clear objectives. Ask yourself:

• What do you hope to achieve with data classification?
• Are you focusing on compliance, data security, or improving data management?
• Which data types are most critical to your business?

Defining these objectives will help you tailor your approach to the specific needs of your organisation, ensuring that the classification process aligns with your overall business goals.

3. Identify and Involve Stakeholders

Data classification is not just an IT responsibility; it requires input from across the organisation. Identify key stakeholders, including:

• IT and security teams who will implement the classification.
• Compliance officers who understand regulatory requirements.
• Department heads who manage the data on a daily basis.
• Legal teams to ensure that classification meets legal standards.

Involving these stakeholders early ensures that the classification process is comprehensive and considers all necessary perspectives.

4. Conduct a Data Inventory

Before you can classify data, you need to know what data you have. A data inventory is a comprehensive list of all the data assets within your organisation. This inventory should include:

• Data types (e.g., customer information, financial records, intellectual property).
• Data sources (e.g., databases, cloud storage, physical files).
• Data location (where the data is stored, whether on-premises or in the cloud).
• Data access points (who has access to the data and from where).

Conducting a thorough data inventory provides a clear picture of your data landscape and is crucial for effective classification.

5. Develop a Classification Framework

A classification framework is a set of guidelines that dictate how data will be categorised. Typically, data is classified into several levels, such as:

• Public: Data that can be freely shared without any risk.
• Internal: Data that is used within the organisation but not shared publicly.
• Confidential: Data that is sensitive and requires protection, such as customer information.
• Restricted: Data that is highly sensitive and access is limited to a few authorised individuals.

Your framework should include clear criteria for each classification level, ensuring consistency across the organisation.

6. Implement Classification Policies and Procedures

Once your framework is established, it’s time to create and implement policies and procedures that support the classification process. These policies should cover:

• Data labelling: How will classified data be labelled and marked?
• Access controls: Who has access to different levels of classified data?
• Data handling: How should data be handled based on its classification level?
• Retention policies: How long will classified data be retained, and when should it be deleted?

Ensure that these policies are communicated clearly to all employees and that training is provided where necessary.

7. Leverage Technology for Automation

Manual data classification can be time-consuming and prone to errors. Leveraging technology can streamline the process and improve accuracy.

Modern data classification solutions, like those offered by Metomic, can automatically classify data based on predefined rules and patterns. These tools can also monitor data in real-time, ensuring that it remains protected according to its classification.

8. Monitor and Review the Classification Process

Data classification is not a one-time task; it requires ongoing monitoring and review. Regularly audit your classification process to ensure that it remains effective and that policies are being followed. Additionally, review your data inventory periodically to account for new data types or changes in the business environment.

9. Continuously Educate and Train Employees

The success of your data classification project depends largely on the awareness and cooperation of your employees. Regular training sessions should be conducted to educate staff on the importance of data classification, how to handle classified data, and how to report any issues.

10. Start Small and Scale Gradually

Starting with a pilot project can be a good approach to data classification. Choose a specific department or data type to classify first, learn from the process, and then gradually expand the classification efforts across the entire organisation. This approach allows you to refine your framework and policies before applying them on a larger scale.

How Metomic can help

Metomic provides a comprehensive suite of tools designed to help businesses identify their data and classify it at scale.

• Data classification tools: Metomic can help you identify and protect sensitive information across various SaaS applications.
• Automated access controls: Metomic ensures only authorised users can access critical data, reducing the risk of data breaches.
• Data retention policies: With Metomic, you can automatically manage and enforce data retention policies to protect sensitive information.
• Visibility and management: You’re able to gain clear visibility into where sensitive data resides within your organisation to effectively manage data security.

Getting started with Metomic

For a more in depth look at what Metomic can do for your organisation, book a personalised demo with Metomic’s team of security experts.

They’ll guide you through the features and benefits of Metomic’s solutions, tailoring advice and strategies to your organisation’s unique needs.