Data Management Glossary
Data Classification
What is data classification?
Data classification is the process of organizing data into tiers of information for data organizational purposes.
Data classification is essential to make data easy to find and retrieve so that your organization can optimize risk management, compliance, and legal requirements. Written guidelines are essential in order to define the categories and criteria to classify your organization’s data. It is also important to define the roles and responsibilities of employees in the data organization structure.
Data classification helps organizations manage data for compliance, security, and operational efficiency. It is especially important for identifying sensitive data such as PII.
How this relates to Komprise:
Komprise provides built-in data classification capabilities powered by its Global Metadatabase, which indexes metadata across all file and object storage. This enables organizations to:
- Identify sensitive, valuable, or redundant data
- Analyze data usage patterns at scale
- Tag and categorize data for governance and compliance
- Curate high-quality datasets for AI and analytics
Because Komprise operates across heterogeneous storage environments, it delivers global, analytics-driven unstructured data classification rather than siloed, system-specific views.
When data classification procedures are established, security standards should also be established to address data lifecycle requirements. Classification should be simple so employees can easily comply with the standard.
Learn more about Komprise data classification.
Examples of types of data classifications:
- 1st Classification: Data that is free to share with the public
- 2nd Classification: Internal data not intended for the public
- 3rd Classification: Sensitive internal data that would negatively impact the organization if disclosed
- 4th Classification: Highly sensitive data that could put an organization at risk
Data classification is a complex process, but automated systems can help streamline this process. The enterprise must create the criteria for classification, outline the roles and responsibilities of employees to maintain the protocols, and implement proper security standards. Properly executed, data classification will provide a framework for the data storage, transmission and retrieval of data.
Automation simplifies data classification by enabling you to dynamically set different filters and classification criteria when viewing data across your storage. For instance, if you wanted to classify all data belonging to users who are no longer at the company as “zombie data,” the Komprise Intelligent Data Management solution will aggregate files that fit into the zombie data criterion to help you quickly classify your data.
How is Komprise data classification different from traditional tools?
Traditional tools often operate within a single system or rely on static scans. Komprise provides a global, continuously updated view of data using its metadatabase and analytics.
Does Komprise require agents to classify data?
No, Komprise performs analytics and classification without agents, reducing complexity and overhead.
Why is data classification important for AI?
It ensures that only relevant, high-quality, and compliant data is used in AI pipelines, improving accuracy and reducing risk.
Data Classification and Komprise Deep Analytics
Komprise Deep Analytics gives data storage administrators and line of business users granular, flexible search capabilities and indexes data creating a Global File Index across file, object and cloud data storage spanning petabytes of unstructured data. Komprise Deep Analytics Actions uses these virtual datasets (see virtual data lake) for systematic, policy-driven data management actions that can feed your data pipelines.
