Why Sensitive Data Discovery is Crucial for Large Companies

In the first few months of 2023, high-profile data breaches occurred at Twitter, PayPal, MailChimp, Reddit, and T-Mobile. Some of these breaches cost hundreds of millions of dollars. Large companies deal with vast amounts of sensitive data on a daily basis. This makes them attractive targets for sophisticated cybercriminals.

Sensitive data includes any information that could cause harm to an individual or organization if exposed. It could be Personally Identifiable Information (PII), financial data, or medical records. It can also include trade secrets or other types of confidential business information. This type of information is valuable to malicious actors.

For that reason, knowing where this information is stored is crucial. Proper data management can have a direct impact on a company’s future. Protecting sensitive data should be a priority for every large company.

What is sensitive data discovery?

Sensitive data discovery is the process of identifying and locating sensitive data. It involves finding this data wherever it resides within a company’s network.

Large companies tend to store large amounts of sensitive data in various locations. It is scattered across different areas within their network and systems. That may include storage systems, databases, applications, or elsewhere.

Every bit of unsecured sensitive data presents an opportunity to malicious actors. Finding all that data and controlling access to it is essential. Sensitive data discovery is the first step to stopping cyber criminals from exploiting sensitive data.

How does sensitive data discovery work?

Sensitive data discovery uses specialized technology to scan, analyze, and classify data. Companies can use predefined criteria to organize sensitive data. Examples of this data include data type, content, location, and access privileges.

Sensitive data may also be classified according to type. Examples of sensitive data include Personally Identifiable Information (PII), financial data, and intellectual property. Protected Health Information (PHI) is a common type of sensitive data. Another example is Payment Card Industry Data Security Standard (PCI-DSS).

Customer information that could identify a person or a household may be considered sensitive data. If it is classified as Consumer Behavior Data, it is also protected.

Why is sensitive data discovery important?

The sensitive data discovery process identifies where all of this critical data is located. It also discovers who can potentially access it. It assesses the value of the information as well as the risks it presents. In other words, it provides your company with the information you need to protect this information.

Having that information is crucial. It enables you to implement more robust security measures. It helps protect the information from unauthorized access and can prevent data breaches.

Data breaches often result in significant financial loss for the company. It can also lead to legal consequences, especially in cases involving regulatory compliance. Last but not least, it can lead to permanent damage to a company’s reputation and credibility.

Data classification is essential to sensitive data discovery

Different kinds of data require different levels of protection. For that reason, data classification is a key component of sensitive data discovery. Data can be categorized based on its level of importance, confidentiality, and sensitivity. It can also be labeled according to any assigned criteria, such as data type or access requirements.

Knowing what types of data you have in your system is fundamental to efficient data management. It informs the decisions you make about how to handle the data and protect it appropriately. It also helps you stay in compliance with data protection regulations.

Automated tools and technologies can quickly and accurately classify and label data. But first, it’s important to establish criteria for data classification for your company. There is no universal standard. Large companies should establish a data classification policy that meets the needs of their data.

One essential but often overlooked step is to involve key stakeholders in the data classification process. That helps ensure that all sensitive data is identified and correctly classified.

Sensitive data discovery helps prevent data leaks

A data leak occurs whenever any sensitive information is disclosed to unauthorized persons. The cause is often due to malicious intent. Cybercriminals employ a myriad of techniques, including hacking, phishing, and social engineering.

But a data leak can also happen because of a simple mistake or human error. Weak passwords, unsecured networks, and third-party vulnerabilities can all lead to breaches. So can lost devices.

That’s why it’s essential to have strong security measures in place to protect sensitive data. Improving data security begins with the process of sensitive data discovery. Identifying your most critical and sensitive data is the first step toward protecting it from potential threats.

Sensitive data discovery enhances risk management

Large companies manage ever-growing volumes of data. But not all of that data needs the same level of protection. The sensitive data discovery process enables companies to prioritize data protection measures. This allows for the more effective management of data related risks.

The discovery process offers large companies a clear understanding of what kinds of sensitive data they possess. They also learn where it is stored and how it is accessed. From this information, they can develop a risk profile of the data. This ensures that the proper resources are allocated to protect the most vulnerable and critical data.

Making informed decisions about data protection strategies reduces the overall risk exposure. This minimizes the likelihood of data breaches, unauthorized access, and other incidents.

Sensitive data discovery supports regulatory compliance

Large companies must remain in compliance with data protection regulations such as GDPR and CCPA. That means a company must know exactly what data they hold, where the data is stored, and who can access it.

Failure to comply with these regulations can have severe consequences. After a data breach, there can be financial penalties and legal liabilities for years to come. Plus, there is also the loss of business caused by bad press and public backlash.

Sensitive data discovery tools can help large companies avoid those problems. They help companies stay in compliance with regulations. Identifying and classifying all sensitive data keeps it protected and mitigates risks.