Which document categories does Zscaler's ML-based data discovery cover? (Select 3)

Which document categories does Zscaler's ML-based data discovery cover? (Select 3)

• A. Insurance policies
• B. Medical records
• C. Legal documents
• D. Images such as passports

Answer: (B)

Zscaler's ML-based data discovery effectively covers a variety of document categories that can include sensitive information requiring scrutiny and compliance with regulations. Medical records are particularly pertinent because they contain personal health information (PHI), which is heavily regulated under laws such as HIPAA in the United States. Given the importance of protecting patient confidentiality and adhering to legal standards regarding health data, the machine learning algorithms are designed to identify and classify this type of sensitive data. Including medical records in the scope of ML-based data discovery is vital for organizations that handle such data, ensuring that they can monitor, manage, and secure it properly. This addresses the need for organizations to understand where sensitive data resides within their infrastructure, helping mitigate risks related to data breaches or non-compliance with regulations. While other document types like insurance policies, legal documents, and images such as passports may also contain sensitive information, the focus here is explicitly on medical records as a distinct category that is crucial for data discovery programs in a compliance-heavy landscape.

Zscaler's ML-based data discovery effectively covers a variety of document categories that can include sensitive information requiring scrutiny and compliance with regulations. Medical records are particularly pertinent because they contain personal health information (PHI), which is heavily regulated under laws such as HIPAA in the United States. Given the importance of protecting patient confidentiality and adhering to legal standards regarding health data, the machine learning algorithms are designed to identify and classify this type of sensitive data.

Including medical records in the scope of ML-based data discovery is vital for organizations that handle such data, ensuring that they can monitor, manage, and secure it properly. This addresses the need for organizations to understand where sensitive data resides within their infrastructure, helping mitigate risks related to data breaches or non-compliance with regulations.

While other document types like insurance policies, legal documents, and images such as passports may also contain sensitive information, the focus here is explicitly on medical records as a distinct category that is crucial for data discovery programs in a compliance-heavy landscape.