Data Classification

Introduction

Not all the data around us, in our devices and networks, is similar or relevant to each other. Without proper classification, it is difficult to navigate the sea of raw data. To solve this emerging issue, data classification was introduced.

Definition

In technical terms, data classification is the process of organizing data in terms of relevant categories such as metadata, file type, and contents. This allows users to find their set of data more efficiently and accurately. Data classification is also implemented to protect related data as different forms of data may require unique protection measures. We can use Active directory to classify data based upon group in Windows.

Types of Data Classification

Data classification can be coupled in terms of different tags and labels attached to the data packages. Each classified data group has a varying level, and type of security protection as data groups are often ranked as per sensitivity. The first three groups of data classification are:

  • Context: When data revolves around any other situation, e.g., location, looks for identity matching etc.
  • Content: When the base classification couples find sensitive data belonging to someone or an organization.
  • User: This form of classification is manually done as the user can choose the type of applications, data packages or virtual intellectual properties they want to group.

In regards to data classification, it is also highly pertinent to implement specific security protections as per the risk level of any potential security breach that may occur to that group of data. This is often common for corporates who have a variety of classified data that needs specialized protection:

  • Low risk (public): If the data is not sensitive and available publicly, the corporates may employ lower security.
  • Moderate risk (private): This form of data is not publicly available however is not very confidential and can be accessed by all employees. E.g., cost of goods, collaboration information, balance sheet.
  • High risk (restricted and confidential): This form of data is extremely confidential and requires superior security. This could be original copies such as blueprints or even pieces of information that are not easy to recover.

Advantages of Data Classification

  • Optimum security is provided for each class of data organized in terms of the potential threat level.
  • Organizes data and information and enhances productivity as it becomes easier for the users to navigate and find their desired information accurately in lesser time.
  • Deletes duplicate, erroneous or stale data which could potentially reduce storage costs (server management).

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