Key points

• Data classification helps IT and security teams identify and manage sensitive data more effectively.
• Without proper classification, organisations risk data breaches, compliance failures, and operational inefficiencies.
• Clear labelling improves visibility, allowing teams to apply the right security controls and respond to threats faster.
• Metomic simplifies data classification within SaaS, ensuring businesses can protect sensitive information with minimal effort.

Data classification involves organising your data to identify and label sensitive information, making it easier to manage and secure. By categorising data appropriately, you gain clearer visibility over what needs to be protected, allowing your team to apply the right security measures.

When done effectively, data classification enhances your ability to monitor sensitive data, enabling quicker responses to potential risks. Setting proper data classification protocols facilitates more accurate enforcement of security policies across your organisation.

However, if data classification is set up incorrectly, you risk exposing your business to data breaches and compliance failures, which can have serious consequences. For example, the consequences of non-compliance can cost a company as much as $14.82 million.

In this article, we'll explore how data classification—through clear labeling and security measures—can mitigate risks and ultimately prevent data breaches and compliance oversights.

How can data be classified and labelled within SaaS?

There are several methods that can be used to classify and label data within SaaS environments. These methods vary in terms of manual versus automated classification, and predefined versus custom labels.

Let's explore these approaches.

1. Manual vs Automated classification

Manual classification requires your team to manually review and label data based on sensitivity. While this can be effective for small datasets, it’s labour-intensive and prone to human error.

In contrast, automated data classification software uses predefined rules and machine learning algorithms to automatically categorise data as it's created or updated. Leveraging automation reduces the chance of human error and ensures more consistent labeling is in place across the board.

2. Predefined labels vs Custom labels

Security professionals have the option of choosing between predefined or custom labels. Predefined labels often include categories such as, "Confidential," "Public," and "Restricted," while custom labels can be tailored to your organisation’s specific needs.

One of the main benefits of predefined labels is that they are quicker to implement and help standardise classification across teams overall. However, while custom labels may require more time to define , they allow more flexibility and can be designed to align with your company’s unique security and compliance requirements.

Developing a comprehensive data classification framework can be a lengthy process. By starting small and expanding, organisations can reduce the risk of data leaks and human error during implementation. Implementing third party solutions like Metomic can help speed up this process through flexible, automated workflows. Book a personalised demo today to see how we can help strengthen your company’s data security.

3. Data classification in SaaS environments

Data classification is essential for protecting sensitive information in SaaS applications like Google Workspace and Slack. These tools enable seamless collaboration, with vast amounts of information shared on them daily.

While restricting data-sharing might seem like a good solution, doing so will only disrupt your team’s productivity.

Luckily, these widely used platforms often support both manual and automated classification, which makes it easier to categorise data as it’s created or shared within the environment.

For example, you could apply labels like "Confidential" or "Restricted" to documents, emails, or files in Google Drive or designate sensitive channels in Slack as "High Risk."

Security teams can then use these labels to identify which data needs additional protection or monitoring. This allows for swift action when a potential risk is detected, such as triggering alerts when sensitive data is shared outside the organisation.

While native tools provide some level of control, they often lack scalability. As organisations adopt more SaaS applications, managing classification and enforcement across multiple platforms become increasingly complex, making it essential to have a centralised data classification solution—like Metomic —for classifying data and setting security rules in one place.

As SaaS tools continue to evolve, automation is becoming a key trend. In 2024, 36% of SaaS management tasks were automated, a rise of 4% from the previous year. This shift towards automation makes it easier for organisations to maintain accurate data classification—as well as saving a lot of time—across all of their SaaS tools, ultimately enhancing their data security posture.

How does data classification provide better sensitive data visibility?

Structured data classification gives security teams a clear overview of where sensitive data is stored, how it moves across systems, and who has access to it.

By labelling information based on its level of sensitivity, teams can quickly locate and track critical data, reducing the risk of it being mishandled or exposed.

1. Faster incident response and fewer security blind spots

With 30% of cloud assets containing sensitive data, lack of visibility can have a severe impact. Proper classification ensures immediate awareness, making data easier to monitor and manage, ultimately making threat detection and response time much faster.

Rather than sifting through vast amounts of unstructured information during an incident, security teams can hone in focus on high-risk areas.

2. Better monitoring and policy enforcement

Classification helps enforce security policies by automatically applying protections based on data type and risk level. For example, documents labelled as "Confidential" can be restricted from being shared externally, while "Internal Use Only" files may trigger alerts if accessed by unauthorised users.

These controls ensure that sensitive information remains protected without relying solely on employees to follow security protocols manually.

🎙️Interview: Everything You Need To Know About Data Classification

In this interview with Metomic's VP of Engineering, Artem Tabalin, we dig deep into how data classification can transform your business' data security

What risks and vulnerabilities can security teams monitor and mitigate effectively with data classification?

Poor data visibility leaves organisations open to risks from accidental exposure to compliance violations. A lack of clear classification can make it difficult for security teams to track sensitive data increasing the risk of unnoticed data breaches.

1. Identifying and prioritising risks

Data classification helps security teams focus their efforts where they matter most. By labelling sensitive data based on its level of risk and location, teams can apply stricter controls to high-risk assets while also allowing lower-risk data to be managed with fewer restrictions. This targeted approach prevents overexposure and makes security processes more efficient.

2. The impact of poor visibility

Misclassified or unclassified data is a major contributor to security incidents. In the public sector, 63% of organisations that don’t classify data at creation take weeks or months to detect misuse. In contrast, 67% of organisations who have implemented data classification processes can spot abnormalities within days or even minutes. This contrast highlights how data classification has a direct impact on response time significantly reducing the window of opportunity for attackers.

3. Learning from data breaches

Several high-profile data breaches, including those involving AT&T, Marriott, and Samsung, have been caused by poor data visibility. Misplaced sensitive files, mislabeled customer records, and unrestricted access to confidential data have all contributed to serious security incidents.

By implementing clear classification policies, organisations can minimise these risks and strengthen their overall security strategy—potentially saving millions, as companies using security AI and automation, including data classification, reduce breach costs by an average of $2.22 million.

Ready to improve your data visibility and security? Book a personalised demo today to see how data classification can help your team identify and mitigate risks effectively.

Data classification strengthens security, supports compliance, and builds confidence with business leaders and stakeholders.

Data classification plays a crucial role in strengthening your organisation’s security posture, ensuring compliance with various regulations, and fostering trust with stakeholders.

Here’s how it works:

1. Maintaining a strong security posture

Data classification helps organisations identify and protect sensitive data. By categorising data based on its sensitivity, businesses can apply appropriate security controls, reducing the risk of breaches. For example, as of 2024, GDPR-related fines have reached nearly €5 billion, with a significant portion of these penalties stemming from companies that failed to protect personal data adequately. This highlights the importance of having proper classification in place to prevent data mishandling which can result in costly mistakes.

2. Simplifying compliance

Proper data classification makes it easier to comply with regulations like GDPR, CCPA, and ISO 27001. By knowing what types of data you have, you can quickly identify what’s subject to specific compliance requirements. For instance, GDPR requires stricter controls over personal data, particularly sensitive information. Data classification helps businesses determine which data falls under these strict requirements, streamlining compliance processes. Organisations that fail to meet these obligations risk substantial fines – such as Meta’s €1.2 billion penalty in 2023 for data protection violations. Clear data classification ensures compliance and reduces the chance of facing similar penalties.

3. Reducing audit and compliance risks

When data is clearly classified, organisations can reduce the risk of compliance failures during audits. By understanding where sensitive data resides and how it’s protected, businesses can avoid penalties and minimise the likelihood of data breaches. Furthermore, a well-structured data classification system demonstrates proactive compliance efforts during audits, reassuring regulators that the organisation is actively managing its data in line with industry standards.

4. Building trust with stakeholders

Demonstrating strong data security and compliance practices enhances trust with customers, partners, and stakeholders. Businesses that take data protection seriously are seen as more reliable and trustworthy. By implementing clear data classification practices, organisations can show they are committed to safeguarding sensitive information, which builds confidence among stakeholders. This transparency not only helps reduce risks but also strengthens relationships and reputation in the market.

🎥How to start your Data Classification process

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.

How Metomic can help

Metomic makes it easier to protect sensitive data, stay compliant, and reduce the workload for your IT and security teams:

• Sensitive data discovery and classification: Metomic automatically finds and classifies sensitive data, making sure it’s organised and protected the way it should be.
• Data loss prevention (DLP): Metomic helps stop unauthorised access to sensitive data, reducing the chances of accidental leaks or breaches.
• Compliance software: Stay on top of regulations like GDPR, CCPA, and ISO 27001. Metomic automates key compliance tasks to make sure your data handling and access controls are up to scratch.
• Access controls: With granular access controls, Metomic helps you manage who can access sensitive data, reducing the risk of insider threats.

With these features, Metomic simplifies security and compliance, lightens the load for your teams, and helps protect your organisation’s most sensitive information.

Getting started with Metomic

Integrating Metomic into your organisation is simple and designed to improve security, streamline compliance, and lighten the load for your IT and security teams. Here’s how you can begin:

• Start with a risk assessment: Take advantage of our free tools to evaluate your current data security measures and spot any gaps. This gives you a clear understanding of potential risks and compliance issues.
• Request a personalised demo: Book a personalised demo. We’ll showcase to you how Metomic works, highlight its key features and explain how it can help strengthen your security, simplify compliance, and protect sensitive data.
• Get expert advice: Have any questions or specific needs? Get in touch! Our team of experts is ready to support you. We’ll work closely with you to integrate Metomic into your systems while ensuring a solid security posture.