SGS and Co., a leading global brand and packaging solutions provider operating in over 20 countries, faced major data management challenges. With a complex network of country-specific, home-grown ERP systems feeding data into an Azure data lake and Snowflake analytics platform, the company aimed to centralize data and generate global KPIs for daily operations. However, reconciling this diverse data landscape proved challenging, further complicated by frequent data quality challenges.

The Challenge: Managing Data Quality and Integration Hurdles in a Global ERP System Landscape

SGS and Co. faced several critical challenges:

• Diverse ERP Systems: The company’s use of various home-grown ERP systems with different technologies made data integration and reconciliation complex and resource-intensive.
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• Frequent Data Quality Issues: Common problems included outliers, incorrect file formats, late file arrivals, structural inconsistencies, long processing times, incomplete datasets, and erroneous master data.
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• Operational Delays: These issues led to delays in generating global KPIs, affecting timely decision-making and overall business performance.
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How 4DAlert Made a Difference

To tackle these challenges, we implemented 4DAlert’s data reconciliation, data quality, and data observability solutions, integrating them with SGS and Co.’s existing Azure data lake and Snowflake analytics platform.

Our Approach Included:

• Automated Data Reconciliation: Deployed 4DAlert to automate data reconciliation processes, significantly reducing manual tasks and errors.
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• Quality Rules Implementation: Established a comprehensive catalog of data quality management and reconciliation rules to ensure accurate and consistent data across all systems.
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• Real-Time Alerts: Set up real-time alerts to monitor data quality issues, schema changes, pipeline performance, and late file arrivals, ensuring timely issue detection and resolution.
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• Data Observability & Pipeline Monitoring: Continuously monitored data pipelines to ensure smooth operation and timely data flow, addressing any issues before they impacted business operations.
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“Managing and reconciling data across our diverse ERP systems was a major challenge. Persistent data quality problems led to delays and impacted our ability to make timely decisions”

Jason Sullivan, Business Intelligence Head, SGS and Co.

4DAlert: Your Solution for Effortless and Accurate Data Reconciliation

4DAlert helps organizations of all sizes streamline their data processes by integrating AI and machine learning to automate data reconciliation, data quality and data observability. 4DAlert automated Data reconciliation and quality checks, ensuring smooth integration whether data in the cloud or on-premises. Are you ready to see the difference that 4DAlert can make? Start your free trial today and see how 4DAlert can improve your data management.