Public Sector — Data Governance and Lineage Management Pipeline

Overview

The purpose of this DAG is to establish robust data governance and lineage tracking mechanisms within the public sector, ensuring data integrity and compliance with regulatory requirements. The pipeline ingests data from various sources, including access logs and sensitive data repositories, to facilitate comprehensive governance controls. The architecture consists of several key processing steps: first, it verifies user access through Role-Based Access Control (RBAC) and Access Control Lists (A

The purpose of this DAG is to establish robust data governance and lineage tracking mechanisms within the public sector, ensuring data integrity and compliance with regulatory requirements. The pipeline ingests data from various sources, including access logs and sensitive data repositories, to facilitate comprehensive governance controls. The architecture consists of several key processing steps: first, it verifies user access through Role-Based Access Control (RBAC) and Access Control Lists (ACL), ensuring that only authorized personnel can access sensitive information. Next, the DAG applies data masking techniques to protect sensitive data during processing. Following this, it tracks data lineage by logging modifications and access events, which is crucial for audit trails. The outputs of this pipeline include detailed lineage reports, access logs, and alerts for unauthorized access attempts. Key performance indicators (KPIs) include the number of unauthorized access attempts and the response time for lineage queries, which help in monitoring the effectiveness of governance controls. In the event of any failures, the system triggers audits to investigate the issues, ensuring continuous improvement and compliance. The business value lies in enhanced data security, improved compliance with regulations, and increased trust in data integrity across public sector operations.

Part of the Customer Personalization solution for the Public Sector industry.

Use cases

• Improved data security and protection of sensitive information
• Enhanced compliance with regulatory standards and requirements
• Increased trust in data integrity among stakeholders
• Streamlined audit processes for quicker issue resolution
• Greater accountability through detailed access and modification logs