Data is not monolithic—its classification and context determine how it should be secured. In this episode, we explore different types of data, including regulated data like personal health information (PHI), payment card information (PCI), and personal identifiable information (PII), as well as trade secrets, intellectual property, and public-facing information. Each type has different legal, operational, and reputational implications if exposed or altered, and thus requires tailored protection strategies. We examine how data classification schemes—ranging from "public" and "internal" to "confidential" and "restricted"—help determine who can access what, and under what conditions. Effective data protection means not just encrypting everything blindly, but understanding the value, sensitivity, and exposure risk of each asset. Whether it’s access control, encryption, masking, or tokenization, the control must match the data. Securing data starts with understanding its purpose, its users, and its risk profile.