How to better protect your data through proper identification.

Do you know what data your organization creates, processes, and/or stores, plus where all that different data lives within your organization? If you don’t, you’re not alone.

Many organizations create, process, and store all kinds of data every day, but do not have a formal data classification process implemented.

For a typical organization, a significant amount of their data is fit for public eyes, but what about client data, employee data, payment card data, or healthcare data? This data requires protections, some common sense, and others regulatory.

Data classification begins with a policy. A steering committee might be in charge of developing or fleshing out a draft for an executive committee or team to sign and adopt. Let’s take a high-level look at data classification to better understand our responsibilities to the data under our control.

 

What Is Data Classification?

Data classification is the process of examining all data within an organization, both structured and unstructured, to separate into different groupings based on contents, file type, metadata, and possibly regulatory requirements. Data stores may contain multiple types of data.

Think of data classification as an inventory of the different data types or classifications across the entire organization.

Different data types will have different levels of sensitivity. The Center for Internet Security (CIS) uses “sensitive”, “business confidential”, and “public” to refer to high, medium, and low data classification sensitivity levels, respectively.

For most organizations, three levels of classification are recommended. Less than three often doesn’t allow for sufficient granularity, leading to inadequate protections. More than three has the potential to create an unnecessary level of complexity.

 

Why Do We Need Data Classification?

Data classification is a mechanism used to identify, mitigate, and manage risk through technology and policy.

It’s important to know where the different data types reside, how the data is used, and what measures need to be put into place to provide adequate protection and meet regulatory requirements.

Another reason for data classification is potential cost savings. Often data is duplicated across multiple data stores, taking up storage for no reason other than it wasn’t known that numerous copies of the same data existed across the organization.

While there are many reasons to classify data, here are a few of the more common reasons:

  • Identify files containing sensitive information
  • Secure critical data
  • Identify duplicate or infrequently accessed data
  • Follow data with regulatory requirements associated with it

 

What Is the Process for Data Classification?

Data classification process implementations vary based on the individual organizations and the purpose or goals of the project. A data classification process will identify existing data and classify it, and it should account for new data being created and/or received.

Here are six simple steps to create a data classification process:

  • Define the purpose of the project and any compliance requirements that apply to the data.
  • Identify the data types within the environment and define the classification levels for the data.
  • Develop a process to regularly scan existing data and a process to account for new data.
  • Develop search criteria such as templates to identify data and validation criteria.
  • Determine what to do with the data classified.
  • Automate or make the process repeatable.

Data classification is a critical component to any organization that creates, processes, or stores data.

It provides a level of confidence knowing what data lives within the organization and provides an organized approach and process to demonstrate adherence to data governance policies for auditors.

Contact a Cybersecurity Expert

Submit a form below or call (713) 401-3380 to discuss your data classification needs with a cybersecurity expert today.

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