Data classification is the process of organizing and labeling data into categories based on file type, contents, and other metadata. Data classification helps organizations answer important questions about their data that inform how they mitigate risk and manage data governance policies. Data classification also enables appropriate protection measures, and efficient search, retrieval and use of each data category12.
While evaluating the data classification process of an organization, an IS auditor’s primary focus should be on whether data is correctly classified. This means that the data is assigned to the appropriate classification level based on its sensitivity, importance, integrity, availability, compliance requirements, and business value. Correct data classification ensures that the data is protected according to its risk level, and that the organization can comply with relevant laws and regulations that apply to different types of data3.
The other three options are not the primary focus of an IS auditor while evaluating the data classification process, although they may be relevant or useful for certain aspects of data management.Data classifications are automated means that the organization uses software tools or algorithms to analyze and label data based on predefined rules or criteria. This can improve the efficiency and consistency of data classification, but it does not guarantee that the data is correctly classified. The IS auditor still needs to verify the accuracy and validity of the automated classifications, and check for any errors or anomalies.
A data dictionary is maintained means that the organization keeps a record of the definitions, formats, sources, and relationships of the data elements in its systems or databases. This can enhance the understanding and usability of the data, but it does not ensure that the data is correctly classified. The IS auditor still needs to examine the content and context of the data, and compare it with the classification criteria and policies.
Data retention requirements are clearly defined means that the organization specifies how long it will keep different types of data, and when it will delete or archive them. This can help reduce storage costs, improve performance, and comply with legal obligations, but it does not ensure that the data is correctly classified. The IS auditor still needs to assess whether the data is stored and protected according to its classification level, and whether the retention periods are appropriate for each type of data.
Therefore, data is correctly classified is the best answer.
References:
Data Classification: The Basics and a 6-Step Checklist - NetApp
What is Data Classification? Guidelines and Process -Varonis
Data Classification and Handling Procedures Guide
