Public Sector — Regulatory Data Taxonomy Construction Pipeline

Overview

The purpose of this DAG is to create a structured taxonomy for regulatory data, which is essential for improving data governance and compliance in the public sector. It integrates various data sources, including internal documents and official publications, to ensure a comprehensive representation of regulatory information. The ingestion pipeline begins with data collection from these sources, followed by a thorough analysis to identify key entities and relationships. Processing steps include en

The purpose of this DAG is to create a structured taxonomy for regulatory data, which is essential for improving data governance and compliance in the public sector. It integrates various data sources, including internal documents and official publications, to ensure a comprehensive representation of regulatory information. The ingestion pipeline begins with data collection from these sources, followed by a thorough analysis to identify key entities and relationships. Processing steps include entity extraction, relationship mapping, and the application of quality control measures to ensure the taxonomy's consistency and relevance. The final taxonomy is stored in a graph-oriented database, facilitating efficient querying and retrieval. Outputs include a semantic search interface that allows users to navigate the taxonomy easily. Monitoring key performance indicators (KPIs) such as data accuracy, completeness, and user engagement metrics ensures ongoing quality management. This DAG delivers significant business value by streamlining regulatory compliance processes, enhancing data accessibility, and supporting informed decision-making within public sector organizations.

Part of the Governance & Compliance solution for the Public Sector industry.

Use cases

• Improves regulatory compliance and governance in public sector
• Increases efficiency in data retrieval and analysis
• Enhances transparency and accountability in data management
• Supports informed decision-making with structured data
• Reduces time spent on manual data organization and retrieval