Life Science — Data Governance for Regulatory Compliance in Life Sciences

Overview

The 'Data Governance for Regulatory Compliance in Life Sciences' DAG is designed to implement robust data governance policies that ensure compliance with regulatory standards in the life sciences industry. The primary purpose of this DAG is to manage access to sensitive data and apply data masking techniques to protect personal information. The data sources include clinical trial data, patient records, and regulatory compliance logs. The ingestion pipeline begins with the extraction of data from

The 'Data Governance for Regulatory Compliance in Life Sciences' DAG is designed to implement robust data governance policies that ensure compliance with regulatory standards in the life sciences industry. The primary purpose of this DAG is to manage access to sensitive data and apply data masking techniques to protect personal information. The data sources include clinical trial data, patient records, and regulatory compliance logs. The ingestion pipeline begins with the extraction of data from these sources, followed by a validation step to ensure data quality and integrity. Processing steps include access management, where permissions are assigned based on user roles, and data masking, which anonymizes sensitive information to prevent unauthorized access. Regular audits are conducted to assess adherence to compliance standards, with key performance indicators (KPIs) such as compliance rates and the number of security incidents tracked to monitor effectiveness. In the event of a compliance failure or security breach, alert mechanisms are in place to facilitate rapid intervention and remediation. The outputs of this DAG include compliance reports, audit logs, and access control records, which are essential for demonstrating regulatory adherence to stakeholders. By implementing this DAG, organizations can significantly reduce the risk of non-compliance, enhance data security, and ultimately improve trust among patients and regulatory bodies.

Part of the Customer Personalization solution for the Life Science industry.

Use cases

• Enhanced data security reduces risk of data breaches
• Improved compliance with regulatory requirements
• Increased trust from patients and regulatory bodies
• Streamlined auditing processes save time and resources
• Better decision-making supported by accurate compliance data