Data Classification and Data Categorisation Data Classification is often used synonymously with Data Categorization. Are they the same? No, they are not. Let us clarify this confusion as these terms are often used interchangeably when in fact they shouldn't. Data Classification and Data Categorisation play important roles in managing and organizing information. However, they serve different purposes and focus on different aspects of data. Here's how they differ: 1. Focus Data Classification focuses on the sensitivity and security of data. It involves grouping data based on how confidential it is, and the legal or ethical obligations associated with its handling. This classification ensures that sensitive information is protected from unauthorized access or disclosure. Data Categorisation focuses on the type and purpose of the data. It organises data based on its content, context, or function (e.g., student data, research data, financial data) to make it easier to manage, analyse, and use. 2. Purpose Data Classification is used to determine how data should be protected and who should have access to it. It ensures that data is handled appropriately in compliance with privacy laws and institutional policies. Data Categorisation is used to organise and structure data based on its type or use, helping to make data easier to retrieve, analyse, and use for academic, administrative, and research purposes. 3. Implementation Data Classification involves assigning a security label to data based on its sensitivity, such as “Public,” “Internal,” “Restricted,” or “Confidential.” These labels dictate how the data is stored, shared, and accessed within the university. Example: Student grades may be classified as “Restricted” to restrict access to authorised personnel only, while general course catalogs might be classified as “Public.” Data Categorisation involves grouping data into categories or types based on its content or role in university operations. This categorisation makes it easier to manage and analyse data for specific purposes (e.g., student records, faculty information, research data). Example: Data might be categorised as “Student Data,” “Research Data,” “Employee Data,” or “Financial Data.” 4. Outcome Data Classification results in the protection of sensitive data by ensuring that access is granted only to those who are authorised, with appropriate security measures such as encryption, access controls, and monitoring. Data Categorisation results in the organisation and structure of data, making it more accessible and useful for various university departments, research initiatives, and decision-making processes. 5. Examples in a University Context Symmetry is a fundamental principle of beauty that describes an object's balanced proportions and the harmony of its parts. Beauty lies in simplicity, as simple designs and forms are more aesthetically pleasing and easier to comprehend. Proportion is the relationship between the different elements of a design and how they relate to one another. Good proportion creates visual harmony and balance. Key Differences Aspect Data Classification Data Catagorisation Primary Focus Data security and sensitivity Data type or function (e.g., student records, research data). Purpose Protect and control access to sensitive data Organize and structure data for academic or administrative use. Outcome Restricted access to sensitive information Easier access and use of data for specific tasks. Examples Student grades (“Restricted”), financial records (“Confidential”) Student data (“Admissions,” “Academic Records”), Research data (“Published,” “Ongoing”) Conclusion While data classification is crucial for ensuring that sensitive data is protected according to its value or sensitivity, data categorization is more about organizing data in a way that makes it easy to analyse and use within the business context. Both are essential for effective data management but address different challenges. Commence Nkomo Chief Data & Analytics Architect Newsletter sign up. Interested in staying updated on IT news? Ensure you're always informed by subscribing. Contact us Each campus has an IT Service Desk. For IT issues, log a fault or contact your campus IT Service Desk. Email us Talk2IT@nwu.ac.za