BY Stephen Cavey | 29 June 2021
Data classification – or the process of categorizing data into relevant subgroups so that it is easier to find, retrieve, and use – is a foundational step to achieving compliance. Yet, it is often overlooked. Not all data is created equal, and classification can help you better understand the varying levels of sensitivity that surround your organization’s data to ensure you remain in compliance with laws such as the GDPR and HIPAA.
We typically classify these levels of data sensitivity into three categories:
The need to classify this data and understand where it falls on the sensitivity scale is key to mitigating risk and making sure all high-risk data is properly secured. So how exactly does data classification work? Organizations can either leverage a user-based manual method, a tool that automates this process, or a hybrid combination of both.
As the traditional method for classifying data, a manual approach requires human intervention. While this method allows files to be viewed and organized in a highly-personalized manner according to your company’s preferences, it is also time-consuming and opens up the possibility of human error. In addition, a manual approach does not give the organization the flexibility to scale and is increasingly difficult to do with the influx of information that businesses are handling today.
As an alternative, organizations can take an automated approach to data classification by leveraging an efficient, technology-driven solution that reduces the degree of human intervention and errors. Depending on the amount of data an organization is dealing with, an automated approach may be the only efficient way for an organization to accurately classify data and make sure all of its information is being accounted for.
More often than not, most classification projects will require some degree of automation, while also enlisting a user-based approach where appropriate. This hybrid method combines the benefits of personalization, with the efficiency and scalability of automation.
Regardless of which approach makes the most sense for your organization, a successful data classification project typically follows a similar process to reaching compliance. The following steps are best practices to keep in mind when embarking on a classification journey:
While this process can be done manually, it evidently consumes a significant amount of time and effort and requires continuous monitoring to be effective. Using an automated data classification tool can help to process large amounts of information more efficiently and synthesize some of these best practices. Embracing the productivity and timeliness of these tools enables organizations to free up more time for team members to focus on what really matters: using this classified information to make informed business decisions, mitigate risk – and ultimately ensure data compliance.
Ground Labs offers Enterprise Recon, a globally recognized solution for data discovery. It is able to detect over 300 data types, it is also agile, which is key to the ever-changing compliance and cybersecurity landscape.
If you are ready to find, classify and harness the power of your company’s data, book a demo with one of Ground Labs’ experts today.
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