What are the Best Steps to Effective Data Classification?

Data protection is not only a legal necessity. It is essential for an organization's survival and profitability. Nowadays, storage has become cheap, and organizations have become data hoarders. And even one day will come when they'll get around mining all of those data and look for something useful.

But, again, data hoarding causes serious issues. And most of what is collected may become redundant, old, or when it is not touched for years.

Moreover, storage might be cheap, but it is not free. And storing a huge amount of data might cost you and, more importantly, increases your risk.

So, suppose your sensitive data is stored digitally, which includes intellectual property, personally identifiable data on the customers or employees, protected health information or financial account information, and credit card details. In that case, these needs are to be properly secured.

So how to protect your data?

Protecting data and comply with data protection and privacy needs like European Union General Data Protection Regulation (GDPR), you need a way with your data that you're collecting and storing. You should be able to determine the importance of those data and see which are useful sensitive data, set policies for handling it, and implement appropriate technical controls or educate users about the ongoing threats to the data that they work and the best practices.

But, again, this is not an easy task, and every organization is different. Therefore you need to know about the role of Data Classification.

What is data classification?

Data classification is one of the crucial steps which allows brands to identify the business value of the unstructured data at the time of creation and separating precious information. It will allow you to make informed decisions about the resource allocation to tackle data from unauthorized access.

Data is divided into multiple groups that share common risks, corresponding security controls required to secure types of groups. Classification tools can be used for improving and promoting sensitive data, which would increase the sensitivity & security of data.

Here are the seven effective steps to Data Classification

Data classification is the foundation of multiple efforts to ensure sensitive data is handled appropriately. This leads to the implementation of becoming more complex and fails to provide any results.

1. Run a risk assessment of sensitive data

To ensure a clear understanding of the organization's regulatory and contractual privacy and confidentiality requirements. Also predefine your data classification objectives through an interview-based approach which involves the key stakeholder, which includes compliance, legal and business unit leaders.

2. Categorize the kinds of data

Resist the urge of granular classification schemes as it tends to cause confusion and more unmanageable. There are three to four reasonable classification categories. Also, make employee roles and responsibilities rock solid. But, make sure the policies and procedures are well defined, easily interpreted by employees, and aligned with the sensitivity of particular.

There are multiple data classification schemes such as

– Public : Data which are freely available to the public.

– Internal : Data which are not meant for public disclosure.

– Confidential : Data which are sensitive and could not be compromised.

– Restricted : Data which are highly sensitive, if compromised, could put the brand at legal or financial risk.

These categories include several types of data along with the handling guidelines and potential risks when compromised.

3. Determine the categories of data

There are multiple kinds of sensitive data that exist in an organization and offer several challenges too. This effort should be organized in the business processes that are driven by process owners. Hence, consider each business process and track it with the flow of data offers insight into what type of data needs to be secured and how it should be protected.

The following questions are

– What kind of customer & partner data do your brands collect?

– What data you create about them?

– What kind of proprietary data do you deal with?

– And what are the collected and created data, and what is confidential?

4. Discover the location of your data

So, after establishing kinds of data in your business, it's important to catalog all of the places where the data is stored digitally. The flow of the data into & out of an organization is the primary point. So, how do your organization store and share data internally or externally? Do you utilize cloud-based services like Dropbox or OneDrive, etc.?

Data discovery tools allow you to generate an inventory of structured data and aid you in understanding where your company's data are stored regardless of any format or location. Also, these tools help you discover the difficulties around identifying data owners by providing insights about your user who are handling the data.

5. Identify and classify data

So after you know where your data is stored, let's get your data identified first and classified later. So, consider your penalties, which are associated with a loss or breach.

Commercial classification tools supports data classification initiatives by facilitating the determination of appropriate classifications and then applying those to classification labels either as a watermark and metadata of an item.

6. Enable the controls

Start enabling control over your data. Establish the baseline cybersecurity measures and define the policy-based controls for each data classification label, which ensures the appropriate solutions are in the right place. High-risk data needs more advanced levels of security and protection, while the risk is lower.

Classification metadata could be used by data loss prevention (DLP), encryption, and other security solutions to determine what data is sensitive and how it should be protected.

7. Maintain and monitor your data

Always be prepared to monitor and maintain the organization's data classification system and making updates when necessary. And classification policies should always be dynamic. And you need to establish a particular process for reviewing and updating, which involves the users to encourage to ensure and adoption your approach continues and meets the changing needs of the business.