Our customer is a leading health-care provider operating a network of hospitals, clinics, and research facilities across the United States. With a mission to deliver high-quality, patient-centered care serving millions of patients annually. The organization relies heavily on data-driven decision-making to enhance patient outcomes.
Handling vast amounts of sensitive patient data, including medical records, treatment plans, and research data, required stringent security measures to comply with HIPAA and other regulations. The
DataOps practices were not built to handle an increasing volume of data. The risk of unauthorized access to sensitive information and data breaches were high given the lack of user authentication. Protecting data in transit and at rest through advanced encryption methods was crucial to prevent data exposure and ensure data integrity.
CloudifyOps implemented Row-Level Security combined with Dynamic Masking in Redshift to control access to rows by defining user roles based on job functions and to hide sensitive data by defining masking rules for columns containing sensitive information.
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