What es data classification?

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Fundamentally, Data Classification entails the sorting or arrangement of data in order of security clearance (confidential, restricted, general use and public) for data security.

However, there are other reasons for data classification which could vary from organization to organization. Data classification is the cornerstone of data management which enables data to be categorized into different classes for facilitated access, data security and to minimize the risk against data leakage.  

The data classification process isn’t just a walk-in-the-park kind of job. It demands attention to detail and proper scrutiny. There are different data classification methods employed as well as different criteria in the arrangement of data from a repository. For the most part, these methods are used for unstructured data which form the bulk of the information owned by an organization and usually becomes one hell of a task to manage.  

Guidelines and Process for Data Classification  

Ideally, any data classification process intended for data security should start with: 

-Definition of Purpose: Why do you want to classify the data? You should understand the importance and objective of categorizing information such as identifying users, documents, and areas. Then decide if you want to classify to facilitate compliance with regulations? Optimize cybersecurity strategy and use of cybersecurity tools? Develop contingency plans? Get a training plan focused on critical users? Define information life cycle? And then you can move into the next below.

-Creation of a Methodology: You’ll need to device a framework that will enable the data classification to work effectively. A process should be put in place to analyze new data and classify them just the way you want it done.  

-Definition of Categories and Classification Criteria: Even if your data classification methodology follows a common structure such as ISO27001, you’ll still need to define the best criteria that adapts to your company. It should fit into your business in terms of policies.

-Definition of Results: What comes next after the data classification? How do you intend using the outcomes of the process? Now that you’ve put everything in place, most importantly, the framework for classifying your data, one of the decisions to make is to grant security clearance or simply put: access, to some staff entitled to critical information about the company. Doing so will require both your discretion and perhaps a few metrics in the likes of trust and integrity. Since the information you would be granting designated staff access to are highly classified, they need to know the file directory of this information, and you need to intimate them on the usage of such sensitive information to avoid chances of abuse. Other essentials of classifying data accordingly for security purposes could be applied here depending on what’s at stake in the company should a data leakage occur.  

Data Leakage and Loss Prevention  

Data leakage is one of the by-products of storing the entire data of an organization in all of its bulkiness in one location. This leads to a data security vulnerability. Attackers can gain access to highly sensitive data stored in the same place with low profile data. This is because there are no restrictions.  


Utilization of Data Classification across the Enterprise   

Data classification process can be utilized in an organization for the following;  

  • Sorting files for data security by classifying them into either restricted, confidential, internal use or public use.  
  • Sorting data according to users access.  
  • Sorting out data into categories by their usage frequency in designated memories

Data Classification Challenges  

The data classification process can be encumbered with some challenges like employee compliance. It is one thing to establish a data classification structure and another to enforce strict compliance on employees especially in large organizations. Another issue is the steep price involved in data classification and a broader context, data management. Establishing the data classification framework on its own is very expensive, and then there is the management cost to ensure continuity.  

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