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Case Study

Global Industrial Tech Leader Boosts Engineering Productivity by 30%

Enhancing operational agility and data trust through DQLabs’ automated observability and enriched lineage capabilities.

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Global Industrial Tech Leader Boosts Engineering Productivity by 30%

Challenges

  • Gaps and inconsistencies in global supply chain data impacting SAP IBP forecast accuracy
  • Fragmented engineering documents with inconsistent metadata causing reuse of outdated files
  • Blind spots and broken job detection issues in dbt and Airflow pipelines slowing root cause analysis
  • Noisy and non-standard sensor data streams complicating integration and analysis

Solution

  • No-code onboarding and intuitive interface enabling faster adoption by business and engineering users
  • Tableau dashboard monitoring with proactive alerts on extract job failures and delays
  • AI-powered anomaly detection and pipeline observability integrated with dbt and Airflow
  • Lineage-aware automation with enriched alerting for faster issue triage and resolution

Results

  • 50% faster root cause analysis and resolution through enriched lineage insights
  • 40%+ reduction in Tableau dashboard refresh failures with minutes-level detection time
  • 25–30% productivity gains across engineering and data teams from automated quality checks

Industry

Industrial Technology

Solutions

Data Observability

Technologies

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Magic Quadrant 2025

Explore how DQLabs accelerates engineering productivity for global industrial tech leaders.

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