Energy — Energy Data Governance Framework

Overview

The Energy Data Governance Framework DAG is designed to establish robust data governance policies within the energy sector, ensuring compliance with industry regulations. The primary purpose of this DAG is to integrate access controls and data masking mechanisms to protect sensitive data while maintaining transparency and traceability. The data pipeline begins with the ingestion of various data sources, including energy consumption logs, regulatory compliance reports, and user access records. Th

The Energy Data Governance Framework DAG is designed to establish robust data governance policies within the energy sector, ensuring compliance with industry regulations. The primary purpose of this DAG is to integrate access controls and data masking mechanisms to protect sensitive data while maintaining transparency and traceability. The data pipeline begins with the ingestion of various data sources, including energy consumption logs, regulatory compliance reports, and user access records. These inputs are processed through a series of steps that include data validation, lineage tracking, and access control enforcement. The processing logic ensures that sensitive information is masked appropriately, and historical data is archived for future audits. Regular audits are scheduled to verify compliance with regulations, and the results are documented in a compliance registry accessible to stakeholders. Monitoring key performance indicators (KPIs) such as data access frequency, compliance audit results, and data masking effectiveness are essential for maintaining governance standards. The business value of this DAG lies in its ability to streamline compliance processes, enhance data security, and provide stakeholders with confidence in data integrity, ultimately leading to improved decision-making and risk management in the energy sector.

Part of the Recommendations solution for the Energy industry.

Use cases

• Enhances data security and privacy for sensitive information
• Streamlines compliance processes to reduce operational risks
• Improves stakeholder confidence in data integrity
• Facilitates informed decision-making through reliable data
• Reduces potential penalties from regulatory non-compliance