Ensuring Data Quality Assurance for Horizon GeoServices

Objective

To enhance the quality of both historical and incoming geospatial data at Horizon GeoServices by implementing automated retrospective and proactive quality checks, ensuring compliance with industry standards. 

Challenges & Approach

Challenges

  • The need to maintain the accuracy and reliability of historical and incoming geospatial data for mission-critical operations. 
  • Managing large datasets and the manual quality assurance process, which was becoming too time-consuming and prone to human error. 
  • Ensuring that new data entering the system met quality standards before ingestion to avoid future data issues. 

VE3’s Approach

  • VE3 applied automated retrospective quality checks to improve the quality of historical datasets by enforcing predefined business and technical rules. 
  • For incoming data, automated quality validation ensured compliance with accuracy, completeness, and currency standards before data ingestion. 
  • Continuous monitoring was implemented to detect and resolve data quality issues in real-time. 

Outcomes

  • Retrospective checks on historical datasets ensured that they complied with quality standards, making them reliable for ongoing use. 
  • New data underwent automated validation before being ingested, preventing quality issues from entering the system. 
  • Continuous monitoring and automated issue resolution allowed Horizon GeoServices to maintain high data quality consistently, ensuring that critical operational decisions were based on reliable datasets. 

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