Data classification is the process of organizing data in groups based on their attributes and characteristics, and then assigning class labels that describe a set of attributes that hold true for the corresponding data sets1. Data classification helps an organization understand the value of its data, determine whether the data is at risk, and implement controls to mitigate risks1. Data classification also helps an organization comply with relevant industry-specific regulatory mandates such as SOX, HIPAA, PCI DSS, and GDPR1.
The most important criteria to consider when developing a data classification scheme are the business criticality and sensitivity of the data2. Business criticality refers to the impact of data loss or compromise on the organization’s operations, reputation, and objectives2. Sensitivityrefers to the level of confidentiality, integrity, and availability required for the data2. Data that is highly critical and sensitive should be classified and protected accordingly, as it poses the highest risk to the organization if mishandled or breached2.
Some of the best practices for data classification are3:
Inventory your data: Identify all data assets within your organization.
Define data categories: Create a classification scheme that suits your organization’s needs.
Assign responsibility: Designate individuals or teams responsible for data classification.
Implement classification tools: Invest in tools and technologies that facilitate data classification.
Educate and train: Raise awareness and provide guidance on data classification policies and procedures.
Review and audit: Monitor and evaluate the effectiveness and compliance of data classification.
References = What is Data Classification? | Best Practices & Data Types | Imperva, What Is Data Classification? The 5 Step Process & Best Practices for Classifying Data | Splunk, Top 10 Best Practices for Securing Your Database - 2023
