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Public Sector — Regulatory Data Extraction for SOP Updates

Free

This DAG extracts regulatory data from various sources to update Standard Operating Procedures (SOPs). By utilizing Named Entity Recognition (NER), it ensures the accuracy and relevance of the extracted data.

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Overview

The primary purpose of this DAG is to automate the extraction of regulatory data from diverse sources, including internal databases and business APIs, to facilitate timely updates of Standard Operating Procedures (SOPs) in the public sector. The architecture consists of an ingestion pipeline that collects data from specified input sources, which are then processed through a series of transformation steps. Initially, the DAG connects to internal databases and APIs to gather relevant regulatory in

The primary purpose of this DAG is to automate the extraction of regulatory data from diverse sources, including internal databases and business APIs, to facilitate timely updates of Standard Operating Procedures (SOPs) in the public sector. The architecture consists of an ingestion pipeline that collects data from specified input sources, which are then processed through a series of transformation steps. Initially, the DAG connects to internal databases and APIs to gather relevant regulatory information. Once the data is ingested, Named Entity Recognition (NER) techniques are employed to identify and extract key regulatory elements, ensuring that only pertinent information is captured. Following extraction, the data undergoes normalization to maintain consistency and is subsequently integrated into a reference database designated for SOP updates. Quality control measures are critical in this workflow; checks are implemented to validate the accuracy of the extracted data, and alerts are triggered in the event of any failures during the process. The outputs of this DAG include updated SOP documents and compliance reports, which are essential for maintaining regulatory adherence. Monitoring key performance indicators (KPIs) such as data accuracy, extraction success rates, and processing times are integral to ensuring the effectiveness of the DAG. By automating this process, the public sector can significantly enhance operational efficiency, reduce manual errors, and ensure compliance with regulatory standards, ultimately delivering greater value to stakeholders.

Part of the Recommendations solution for the Public Sector industry.

Use cases

  • Increases operational efficiency in regulatory compliance
  • Reduces manual errors in data processing
  • Ensures timely updates of SOPs to meet regulations
  • Enhances data accuracy through automated checks
  • Facilitates better decision-making with reliable data

Technical Specifications

Inputs

  • • Internal regulatory databases
  • • Business API data feeds
  • • Compliance documentation repositories

Outputs

  • • Updated Standard Operating Procedures (SOPs)
  • • Compliance reports for regulatory audits
  • • Data quality assurance logs

Processing Steps

  1. 1. Connect to internal databases for data extraction
  2. 2. Fetch data from business APIs
  3. 3. Apply Named Entity Recognition to identify key elements
  4. 4. Normalize extracted data for consistency
  5. 5. Integrate data into the reference database
  6. 6. Perform quality control checks on the data
  7. 7. Generate updated SOPs and compliance reports

Additional Information

DAG ID

WK-0178

Last Updated

2026-01-26

Downloads

44

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