If data is considered the crown jewels of an organization, managing and protecting information is paramount. With increasingly stringent regulations, such as the General Data Protection Regulation (“GDPR”), it is imperative that organizations have a sound approach to effectively manage both structured and unstructured data. One powerful tool that helps organizations with this process is data classification.
What is data classification?
Data classification is the process of identifying and labeling data based on their sensitivity and assigning appropriate security measures. Data classification prioritizes protection of valuable information, and helps organizations comply with privacy laws such as the GDPR.
Structured vs. unstructured data:
Structured data:
These data are those organized in a database with a clearly defined structure, such as tables in a spreadsheet or fields in a database. Examples include customer information, transaction data and financial reports.
Unstructured data:
Unstructured data has no predetermined data model or organizational structure. This includes documents, emails, images and other unorganized information often scattered across different platforms and systems.
Benefits of data classification:
More accurate security: It enables targeted security measures by classifying data by sensitivity, such as encryption or access control.
Regulatory compliance: Data classification supports organizations in meeting the complex requirements of data protection legislation, such as the GDPR. It helps identify and protect personal data.
Efficient data management: Organizations can manage their data more effectively because data classification helps identify obsolete, redundant or irrelevant data.
Awareness and training: By making employees aware of data classification, organizations can create a culture of data awareness. Employees better understand what information is considered sensitive.
Incident response: In the event of a data leak or breach, data classification allows organizations to respond quickly, determine the scope of the incident and take appropriate remedial action.
Implementation of data classification:
Identification of sensitive data: Identify which data is considered sensitive and requires a higher level of protection.
Classification labels: Assign classification labels to data based on their sensitivity, such as “Public,” “Internal,” and “Confidential.”
Automation: Consider using automated data classification tools to speed up the process and minimize errors.
Periodic review: regularly review and update data classification to ensure it remains accurate in a changing business environment.
Data classification is a key element in today’s data management landscape, where privacy and security are of paramount importance. Classify structured and unstructured data for legal compliance and a robust data security strategy to protect information. Data classification as an integral part of data management promotes a secure, organized and AVG-compliant business environment.
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