AI-Driven Data Quality Monitoring Solution

DQM for commercial pharma
Solution Snowflake
Solution Snowflake
Industry Pharma & Life Sciences
Region US
Technology Snowflake
Context
To address persistent data governance challenges and inefficiencies in issue resolution, a global healthcare company partnered with MathCo to implement an AI-driven data quality monitoring solution powered by GenAI. The organization faced recurring issues across domains, lengthy manual reporting cycles, and limited visibility into root causes. By consolidating issue tickets, enriching data context, and applying large language models to detect systemic patterns, the solution reduced manual effort by 87% and improved root cause analysis by 40%. Real-time dashboards enabled cross-functional teams to act on insights and strengthen compliance across systems.
Problem statement

A global Swiss healthcare company faced persistent data quality issues within its governance and compliance team. Limited visibility into issue types, frequency, and root causes led to delays in identifying and resolving hotspots. These challenges spanned domains, affecting regulatory reporting, operations, and analytics. Cross-functional teams struggled to prioritize issues systematically. Manual reporting processes consumed over 15 hours per cycle and lacked the precision for proactive remediation, hindering timely decision-making and reducing overall efficiency across critical business functions.

Impact

  • 40% Reduction in Time to Root Cause: The AI-powered insights engine significantly accelerated the process of identifying hotspots and underlying issues. 
  • Manual Effort Cut by ~87%: Operational reporting time dropped from 15+ hours to just 2 hours, freeing up expert resources to focus on more strategic tasks. 

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