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Data Classification
Data Classification

What are the Major Steps of Data Classification?

Suppose you are a big brand and your users create millions of files. Most of the data are highly sensitive, and if stolen or experience, any breach could cause a significant loss to your company. Data classification tags data such as type, sensitivity, and value to the organization when stolen or destroyed. 

Data classification aids the organization in understanding its value and determine whether it is at risk and implement control to reduce it.
There are various types of data classifications on the basis of context, content, and user selections.

– Content-based classification: It involves files and document reviews and classifying them

– Context-based classification: It involves classifying files based on metadata, such as the application that created the file or the person who created the document, or the location in which the files were authored or modified. 

– User-based classification: It involves classifying files according to a manual judgment of educated users. People who work with documents could specify how sensitive they are when creating a document after an important review or edit. 

Now, let’s focus on the steps of data classification

1. Determine the project gals

The desired outcome of the project is when you reach your goals. And to achieve it, you must make sure you define your goals correctly. 

And to do that, you must ensure you collect the right information. It’s best that you concentrate on the initial efforts. 

2. Categorize the types of data

It would be best when you determined the types of sensitive data in your organization that can present challenges. This kind of effort should be organized around your business processes and driven by process owners. 

Hence these are the considerations you should take

-What kind of customer and partner data does your brand collect? 

– What data should you create about them?

– What kind of proprietary data should you create? 

– What transactional data do you should deal with?

– What is confidential- collected & created data? 

4. Discover the location of data

After knowing the data types in your company, you must catalog all the places where your data is stored. The flow of data with in and out of the organization is a significant consideration. So, how do your organization store and share data internally and externally? 

Data discovery tools aids in generating an inventory of unstructured data help you understand exactly where your company’s data are stored, inconsiderate of location or format. 

5. Identify and classify data

When you know your data is stored, you must know how to classify it and protect it appropriately. So, consider the penalties associated with the loss or breach. For instance, what kind of fines could be levied per record for a HIPAA preach which involves protecting the health data? Insights of the potential costs are associated with the compromise of a data set, which will enable you to set expectations for the price for protecting it and the classification level to set. 

Advanced classifications systems offer user-driven, system-suggested, and also automated capabilities

– Provisions of a menu of tailored data classification options 

– Through Automation, the system selects the appropriate classification on the basis of analysis engines with limited user inputs

6.Enable the controls

Establish your baseline cybersecurity measures and define the policy-based controls for each data classification label to appropriately ensure the solutions. High-risk data needs more advanced levels of protection, while lower-risk data needs less protection. Metadata classification can be used by data loss prevention, encryption, security solutions, and more to determine which data are sensitive and how it can be protected. 

7. Monitor and maintain your data

You must be prepared to maintain and monitor the company’s data and classification system and also make necessary updates. Classification policies must be dynamic. You need to establish a proper process for reviewing the update, which involves the user encouraging the adoption and ensuring the approach that continues to meet the business’s changing requirements.   

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