Data classification can be a daunting process, especially for firms that lack robust practice in place. Data classification is critical and challenging to avoid, as with any security strategy. Whether or not the value is recognized, it may be moved farther and further down the priority list in favor of topics that are easier to resolve.
We’ll help you make a case for data classification in this post and fill in some critical knowledge gaps to guarantee your strategy is complete. It will necessitate an investment of resources, mainly time, money, and personnel, but it will help firms avoid costly mistakes in the long run.
What Exactly is Data Classification
A modern organization’s lifeblood is data. Regardless of your industry or service, your information is critical to the success of your organization. As a result, ensuring that your data is secure and readily available to the appropriate persons is vital.
At its most basic, data categorization relates to categorizing your data into categories to aid in accessing, utilizing, leveraging, and securing it effectively. When your data is classified correctly, it is easy to find and recover when needed. It is especially pertinent to risk management, compliance, and data security.
Data classification is based on best practices for categorization, which include the use of visual and metadata labels that are tied to predetermined criteria. Of course, you can’t classify something you don’t understand. To begin, you must concentrate on data discovery to determine the scope. In today’s modern world, data can be found in various locations, all of which are equally significant. Look at the endpoint, databases, network shares, and the cloud.
Methods of Data Classification
When deciding on data classification, the first step is determining what strategy to take. Each method provides insight into organizational data and can be integrated to strengthen security and reduce the possibility of unintentional or purposeful misclassification.
For sensitive material, Content-Based Classification inspects and interprets file data. This approach employs regular expression and fingerprinting to provide an answer to the inquiry, “What’s in this document?”
Context-Based Classification identifies sensitive information by pointing to apps, places, creators, or other variables.
To identify sensitive data and documents, User-Driven Classification relies on end-user and manual choice based on the user’s experience and discretion at the moment of creation, editing, or review. A well-defined workflow is required for this strategy.
Gartner suggests that organizations employ a collaborative approach to incorporate the abovementioned strategies. Chief Data Officers (CDOs) should develop and use classification skills jointly to identify, tag, and store all data. Coverage and dependability will be ensured by a combination of user-driven and automatic classification.
How to Choose a Data Classification System
Look for the following characteristics:
Search for compound terms
Reduces false positives and false negatives, increasing accuracy.
Index
Allows you to identify sensitive terms without having to re-crawl the data.
Adaptable taxonomy manager
It is simple to add and alter terms and rules.
Flows of work
When a document is categorized in a given way, it takes specific actions automatically. A procedure, for example, may relocate sensitive material away from a public share.
Coverage breadth
Cloud and on-premises data classification sources are supported, as well as organized and unstructured data.
