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Automation of Operational Report Verification for Large-Scale PDF Data Processing
  1. case
  2. Automation of Operational Report Verification for Large-Scale PDF Data Processing

Automation of Operational Report Verification for Large-Scale PDF Data Processing

altkomsoftware.com
Energy & natural resources
Manufacturing
Supply Chain

Identifying Challenges in Manual Verification of Diverse Large-Volume PDF Reports

The client faces significant inefficiencies in manually analyzing and verifying up to 3,000 daily operational PDF reports, which are highly diverse in structure and content. This manual process is time-consuming, prone to human error, and hampers timely data insights, reducing operational efficiency and increasing risk of missing critical information.

About the Client

A large energy company involved in oil and gas operations, managing extensive operational reports and data sources.

Goals for Automating PDF Data Extraction and Reporting

  • Develop an automated system to extract specified data fields from diverse PDF reports and feed this data into a centralized database.
  • Reduce manual verification time from several hours to under one hour per day.
  • Eliminate human errors associated with manual data entry and review processes.
  • Implement continuous monitoring that automatically detects new reports and processes them at regular intervals.
  • Create an interactive dashboard that provides filtered, aggregated, and historical operational data for quick decision-making and trend analysis.

Core Functionalities for Automated PDF Data Extraction and Analysis

  • Automated import of incoming PDF files into a designated processing folder.
  • Configurable algorithms to search for keywords and extract data based on defined coordinates within varied report formats.
  • Continuous background monitoring to detect and process new incoming reports every few minutes.
  • Data validation mechanisms to ensure accuracy of extracted data before entry into the database.
  • Secure and scalable database to store current and historical report data.
  • Integration with an analytics dashboard, enabling filtering, trend analysis, and historical reporting.
  • Ability to modify extraction parameters and keywords without system overhaul.

Recommended Technologies and Architectural Approaches

.NET framework for software development
SQL or scalable relational database system
Power BI or equivalent for analytical dashboards
Cloud storage and processing (e.g., Azure or similar cloud platform)

External System Integrations for Data and Workflow Automation

  • PDF file storage location for automated file detection
  • Database systems for data storage and retrieval
  • Dashboard platform for data visualization
  • Notification systems for process status alerts

Key Non-Functional System Requirements

  • System should process up to 3,000 reports daily with minimal latency
  • High accuracy in data extraction, aiming for 100% correctness through validation checks
  • System availability of 99.9% uptime to support continuous operations
  • System must be scalable to accommodate potential growth in volume or report complexity
  • Ensure data security and user access controls aligned with industry standards

Expected Business Impact of the Automated Report Verification System

Implementing this automated verification system will significantly reduce manual processing time from several hours to less than one hour per day, leading to operational time savings of approximately three hours daily. It will ensure 0% human error in report verification, improving data accuracy. Enhanced automation and analytics capabilities will enable rapid insights, trend analysis, and historical data review, thereby optimizing decision-making and reducing operational risks.

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