Data Integrity for a F500 Agricultural Machinery Global Leader

The Challenge

• Frequent data loss while transferring data across systems due to format inconsistencies, latency, and sync failures.
• Lack of visibility into real-time data movement, making it difficult to track inconsistencies.
• High cost of downtime due to errors in business-critical reports and analytics.

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The Solution

• Data Monitoring across multiple data sources
• Data Reconciliation checking
• Schema & Consistency Checks: Ensured data structure remained uniform while moving across databases.
• Real-time Anomaly Detection: Leveraged Kafka-based monitoring to flag potential data mismatches before they impacted operations.
• Implemented Datachecks to perform automated data diff analysis between source and target systems. Datachecks quickly identified inconsistencies, allowing for immediate corrective action before they cascaded into business impacts.

The Impact

• Data Downtime Reduced by 90% with proactive error detection.
• Eliminated Silent Data Corruption through real-time validation.
• Reduce time to action by 30%.

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