Retail — Automated Literature Review Corpus Ingestion Pipeline

Overview

The primary purpose of this DAG is to facilitate the automated ingestion of various corpora from multiple sources, including internal databases, PDF documents, and APIs. By normalizing the ingested data, the DAG ensures high quality and traceability, which are critical for effective knowledge management in the retail sector. The ingestion pipeline begins with data extraction from specified sources, followed by expert validation to ensure accuracy and relevance. After validation, the data is inte

The primary purpose of this DAG is to facilitate the automated ingestion of various corpora from multiple sources, including internal databases, PDF documents, and APIs. By normalizing the ingested data, the DAG ensures high quality and traceability, which are critical for effective knowledge management in the retail sector. The ingestion pipeline begins with data extraction from specified sources, followed by expert validation to ensure accuracy and relevance. After validation, the data is integrated into a knowledge management system, where it can be easily accessed and utilized for literature reviews. Quality control measures are implemented throughout the process, including error tracking and recovery mechanisms to handle ingestion failures. Key performance indicators (KPIs) such as ingestion time and error rates are monitored to assess the efficiency and reliability of the pipeline. By streamlining the literature review process, this DAG provides significant business value by enabling retail organizations to make informed decisions based on comprehensive and up-to-date information.

Part of the Knowledge Portal & Ontologies solution for the Retail industry.

Use cases

• Increased efficiency in literature review processes
• Improved data quality and reliability for decision-making
• Enhanced compliance with security standards
• Faster access to relevant information for stakeholders
• Streamlined workflows reduce manual intervention