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  • 14 March 2024
  • 10 min read

The many organisational benefits of data classification

What is data classification? Why should organisations classify their data? And what are the pros and cons of manual classification vs automated classification?
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Only 54% of companies know where their sensitive data is stored – we call this “dark data” and it poses a vast number of cyber security risks and threats for organisations and their employees … and, once again, highlights the importance and many organisational benefits of data classification.

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Data classification is not merely about sorting bits and bytes; it is about orchestrating a symphony of security measures to safeguard the lifeblood of any organisation: its data.

Let us embark on a journey to unravel the intricacies of data classification, understanding its significance in fortifying organisational defences and fostering a culture of cyber resilience.

What is Data Classification?

What is data classification

Data classification is the systematic process of categorising and organising data based on its sensitivity, importance, and confidentiality levels. This categorisation allows organisations to better understand and manage their data assets, ensuring appropriate protection measures are applied to mitigate potential risks.

Data classification involves assigning labels, tags, or metadata to data sets, indicating their level of sensitivity and the degree of protection required. These labels typically range from public information, which is readily accessible to anyone, to highly sensitive data, which requires stringent access controls and encryption to safeguard its confidentiality.

Data classification serves as the foundation of a robust data security strategy, enabling organisations to identify, protect, and manage their data assets in a manner that minimises the risk of unauthorised access, data breaches, and regulatory non-compliance.

Why Should Organisations Classify Their Data?

Data classification is not merely a bureaucratic exercise; it is a strategic imperative for organisations seeking to fortify their defences against cyber threats and enhance their overall data management practices. 

Organisational data classification

The benefits include:

  • Safeguards Corporate and Client Data: Data classification enables organisations to identify and prioritise their most sensitive information, ensuring that appropriate security measures are implemented to safeguard against unauthorised access, data breaches, and cyber-attacks.
  • Improves Incident Response Time: In the event of a security incident or data breach, time is of the essence. With a well-established data classification framework in place, organisations can expedite their incident response efforts by swiftly identifying the compromised data and implementing targeted remediation measures, proactively minimising the impact of the breach, reducing downtime, and enhancing the organisation's resilience to cyber threats.
  • Understand What Data You Hold and Where: Data classification provides clarity on the types of data held by the organisation, their locations, and their associated risks. By cataloguing and mapping out data repositories, organisations gain valuable insights into their data assets, facilitating better data governance, compliance efforts, and strategic decision-making.
  • Control Access to Data: classification allows organisations to enforce granular access controls based on the sensitivity of the data. By defining who has access to what data and implementing robust authentication mechanisms, organisations can mitigate the risk of insider threats, unauthorised access, and data leakage. This ensures that only authorised personnel can access sensitive information.
  • Decrease Sensitive Data Footprint: Data proliferation is a common challenge faced by organisations, leading to increased exposure to cyber threats and regulatory compliance risks. Through data classification, organisations can identify redundant, obsolete, or trivial data (ROT) and streamline their data repositories. By reducing their sensitive data footprint, organisations can minimise their exposure to potential threats, optimise storage resources, and simplify data management processes.
  • Optimise Cost and Minimise Wastage on Irrelevant Data: Managing vast volumes of data incurs significant costs, both in terms of storage resources and operational overheads. Data classification enables organisations to prioritise their data management efforts, focusing resources on securing critical data assets while minimising wastage on irrelevant or low-value data.
  • Boost Operation and Employee Efficiency: With a well-structured data classification framework in place, employees can quickly locate and access the information they need, without wasting time sifting through vast data repositories. This streamlines workflow processes, enhances collaboration, and empowers employees to make informed decisions based on accurate and reliable data.
  • Lowers Regulatory Risks/Fines, Lowers Reputational Risks: Data classification helps organisations demonstrate compliance by ensuring that sensitive data is handled in accordance with regulatory requirements and industry standards. By adhering to data classification best practices, organisations can mitigate the risk of regulatory fines, legal liabilities, and reputational damage associated with data breaches or non-compliance incidents.
  • Fosters a Security-Aware Culture: Data classification initiatives provide an opportunity to educate employees about the importance of data protection and their role in safeguarding sensitive information. By involving employees in the data classification process and providing training on security best practices, organisations can foster a culture of security awareness, where employees are vigilant, proactive, and committed to upholding data security standards.

How Data Classification Can Help Mitigate Insider Threats

Insider threats, whether malicious or unintentional, pose significant risks to organisational security and data integrity. While traditional security measures focus on defending against external threats, insider threats often go undetected and can cause substantial harm from within.

Mitigate Insider Risks and Threats

Data classification plays a pivotal role in mitigating insider threats by providing organisations with the means to identify, monitor, and control access to sensitive information.

Here's how data classification can help mitigate insider threats:

  • Identify Insider Threat Risks: Data classification enables organisations to identify potential insider threat risks by categorising data based on its sensitivity and criticality. By assigning classification labels to data sets, organisations can pinpoint high-value assets that are most vulnerable to insider threats. This proactive approach allows organisations to allocate resources effectively to protect their most valuable data assets.
  • Monitor Data Access and Usage: Effective data classification facilitates granular access controls, allowing organisations to monitor and track user access to sensitive information. By implementing role-based access controls (RBAC) and attribute-based access controls (ABAC), organisations can restrict access to sensitive data to authorised individuals only. Monitoring tools can track user activity, identify suspicious behaviour patterns, and generate alerts in real-time, enabling organisations to detect and respond to potential insider threats promptly.
  • Enforce Least Privilege Principle: The principle of least privilege dictates that users should be granted only the minimum level of access necessary to perform their job functions. Data classification facilitates the implementation of least privilege access controls by categorising data according to its sensitivity level. By restricting access to sensitive data on a need-to-know basis, organisations can reduce the risk of insider threats and limit the potential impact of unauthorised access.
  • Educate Employees on Security Policies and Best Practices: Data classification initiatives provide an opportunity to educate employees about security policies, data handling best practices, and the consequences of insider threats. Training programs should cover topics such as recognising suspicious behaviour, reporting security incidents, and adhering to data classification guidelines. By fostering a culture of security awareness, organisations can empower employees to become active participants in preventing insider threats and protecting sensitive information.

The Pros and Cons of Automated Data Classification vs Manual Data Classification

Pros vs Cons of data classification

When it comes to implementing data classification, organisations must decide between automated and manual approaches. Each method offers unique advantages and disadvantages, which must be carefully considered based on the organisation's specific needs and resources.

Automated Data Classification:

Automated data classification utilises machine learning algorithms, pattern recognition techniques, and predefined rules to analyse data content and assign classification labels automatically.


  • Efficiency and Scalability: Automated data classification can process large volumes of data quickly and efficiently, making it suitable for organisations with extensive data repositories. This scalability ensures that classification tasks can be completed in a timely manner, even as data volumes grow.
  • Consistency and Accuracy: Machine learning algorithms can analyse data patterns consistently and accurately, reducing the likelihood of human error associated with manual classification. This consistency ensures that classification labels are applied uniformly across all data sets, maintaining data integrity and compliance.
  • Cost-Effectiveness: While initial implementation costs may be higher due to investment in software and infrastructure, automated data classification offers long-term cost savings by reducing the need for manual labour and streamlining classification processes.
  • Real-time Classification: Automated classification tools can analyse data in real-time as it is created or ingested into the system, ensuring that data is classified promptly and in accordance with predefined rules and policies.


  • Lack of Contextual Understanding: Automated classification tools may lack the contextual understanding necessary to accurately classify data based on its business context, semantics, or user intent. As a result, misclassifications may occur, requiring manual review and intervention.
  • Complexity of Implementation: Implementing automated data classification requires expertise in machine learning, data science, and information security. Organisations may face challenges in configuring and fine-tuning classification algorithms to suit their specific requirements.
  • Dependency on Training Data: Machine learning algorithms rely on training data to learn patterns and make classification decisions. Organisations must ensure that training data is representative and up to date to achieve optimal classification accuracy.

Manual Data Classification:

Manual data classification involves human intervention to review, analyse, and assign classification labels to data sets based on predefined criteria.


  • Contextual Understanding: Human reviewers possess the contextual understanding necessary to interpret data content, semantics, and user intent accurately. Manual classification allows for nuanced decision-making based on business context and organisational knowledge.
  • Flexibility and Adaptability: Manual classification allows organisations to tailor classification criteria and policies to suit their specific business requirements and regulatory compliance needs. This flexibility enables organisations to accommodate diverse data types and classification scenarios effectively.
  • Accuracy in Complex Cases: In cases where data classification requires subjective judgment or domain expertise, manual classification may yield more accurate results than automated methods. Human reviewers can apply nuanced decision-making and resolve ambiguous classification scenarios effectively.


  • Resource Intensive: Manual data classification can be time-consuming and resource-intensive, particularly for organisations with large volumes of data. The manual review process may result in delays and bottlenecks, impacting overall efficiency and productivity.
  • Inconsistency and Variability: Human reviewers may apply classification labels inconsistently or subjectively, leading to discrepancies in data classification across different reviewers or departments. This inconsistency can compromise data integrity and compliance with regulatory requirements.
  • Scalability Challenges: Manual classification may not be scalable to accommodate the growing volume and complexity of data in modern organisations. As data volumes increase, manual classification efforts may become unsustainable, requiring additional resources and labour.

Both automated and manual data classification approaches offer distinct advantages and disadvantages. Organisations must carefully evaluate their specific requirements, resources, and priorities to determine the most suitable approach for their data classification needs. Ultimately, a combination of automated and manual classification may offer the best balance of speed, accuracy, and adaptability for organisations seeking to optimise their data management and security strategies.

The Importance of Senior Executive Buy-In in Data Classification Initiatives

Senior executives play a pivotal role in setting strategic direction, allocating resources, and championing organisational priorities.

Board engagement with data classification initiatives

Here is why engaging the board and securing their support is essential for the success of data classification initiatives:

  • Alignment with Organisational Goals and Priorities: By obtaining senior executive buy-in for data classification initiatives, organisations can demonstrate the strategic importance of data security and compliance in achieving organisational objectives. This alignment fosters a culture of accountability and commitment to data protection across all levels of the organisation.
  • Allocation of Resources and Budgets: Data classification initiatives require adequate resources, including funding, technology infrastructure, and personnel, to be successful. Senior executives have the authority to allocate resources and budgets to support data classification efforts effectively. By securing senior executive buy-in, organisations can ensure that sufficient resources are allocated to implement and sustain data classification programs.
  • Leadership and Advocacy: Senior executives serve as advocates and ambassadors for data classification initiatives, championing the importance of data security and compliance within the organisation. By visibly supporting data classification efforts, senior executives set a tone of urgency and priority, encouraging widespread adoption and adherence to classification policies and procedures. Senior executive support lends credibility and legitimacy to data classification efforts, reinforcing the importance of data security as a strategic imperative for the organisation.

By aligning with organisational goals, allocating resources, providing leadership and advocacy, managing risks and compliance, and fostering communication and transparency, senior executives can drive meaningful progress towards establishing a robust data classification framework that protects sensitive information, enhances organisational resilience, and promotes a culture of data security and compliance across the organisation.


Data classification serves as the cornerstone of a comprehensive data security strategy, enabling organisations to identify, protect, and manage their data assets effectively. By categorising data based on its sensitivity and implementing appropriate security measures, organisations can safeguard against cyber threats, mitigate insider risks, and ensure compliance with regulatory requirements.

Moreover, the benefits of data classification extend beyond security, encompassing operational efficiency, cost optimisation, and enhanced decision-making. By understanding the types and locations of their data, organisations can streamline data management processes, minimise wastage, and empower employees to access accurate information efficiently.

Whether through automated or manual approaches, the implementation of data classification requires commitment and support from senior executives. By aligning with organisational goals, allocating resources, and providing leadership and advocacy, senior executives can drive meaningful progress towards establishing a robust data classification framework.

As organizations embark on this journey to unravel the intricacies of data classification, they pave the way for a future where data security is not just a priority but a fundamental aspect of organisational culture and resilience in the face of evolving cyber threats.

Working with the right partner

Partnering with a trusted cyber security training and awareness company, such as The Security Company Ltd. (TSC), is crucial. With 25 years of experience, TSC specialises in enhancing security behaviours, fostering a robust security culture, and raising awareness of threats and risks across global organisations.

The dynamic nature of cyber threats necessitates a comprehensive and adaptive cyber security strategy for all organisations. By understanding the evolving threat landscape and investing in robust training and awareness initiatives, decision-makers can fortify their organisations against potential risks and cyberattacks.

At The Security Company, we specialise in boosting cyber awareness, targeted training, customised projects and role-based solutions. Through our tailored subscription services, targeted and customised eLearning and awareness materials and our behavioural assessments, we're committed to helping organisations like yours instil long-term, security-conscious behaviours.

Our method is distinct. We begin by diving deep into your team's current mindset, pinpointing lax behaviours, security gaps and departments in need of focus and attention. From there, we craft tailored solutions that encourage better cyber practices from your employees. With comprehensive training and seamless integration into your current systems, we're here to fortify your team against modern cyber threats and be your trusted cyber security and awareness partner.

Ready to take the next step?

We can help you to formulate an effective and comprehensive cyber security training and awareness program for your organisation year-round and be your dedicated partner for employee behaviour change and, ultimately, security culture change.

Do not hesitate to contact us for further information.

Written by
Nas Ali
Cyber security and awareness content creator focused on emerging threats and the next wave of cyber security risks like AI, deepfakes and tech 4.0 initiatives in order to build towards a more secure organisational culture.
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