Transforming Enterprise Data Pipelines With Intelligent Automation
Exathought enables seamless data integration and quality assurance by replacing legacy .NET processes with Talend, ensuring real-time monitoring, automated reconciliation, and scalable ETL orchestration.
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Paving the way to reliable, scalable, and accurate data processing for a global enterprise
At a glance
INDUSTRY
Data Engineering / Enterprise IT
LOCATION
CHALLENGE
Legacy ETL processes lacked automation, monitoring, and scalability, leading to deadlocks, delayed ingestion, and manual issue detection
Global
SUCCESS HIGHLIGHTS
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Automated orchestration with Talend
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Real-time alerts and notifications
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Functional Data Reconciliation (FDR) across all ETL stages
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Scalable ingestion and staging across environments
The Challenge
The client relied on legacy .NET-based ETL jobs scheduled at fixed intervals. As data volumes grew and database performance fluctuated, overlapping job executions caused deadlocks and ingestion failures. Additionally:
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No automated alerts for job failures
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Manual monitoring delayed issue resolution
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Failed jobs led to missed data ingestion until the next day
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The client needed a robust, automated, and monitored ETL framework to ensure timely and accurate data processing.
Our approach
Exathought implemented a comprehensive QA and orchestration strategy using Talend and AWS services:
Talend-Based Orchestration
Replaced legacy .NET programs with Talend jobs for file retrieval, ingestion, and staging.
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Automated Monitoring & Notifications
Integrated Slack-based alerts for success and failure across all ETL phases.
Functional Data Reconciliation (FDR)
Used Right Data Tool (RDt) to validate record counts and data integrity across SFTP, S3, Athena, staging, and target layers.
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Multi-Stage QA Validation
Verified data consistency at each stage - file retrieval, ingestion, staging, and final load - using custom queries and reconciliation scripts.
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Parallel Glue Job Execution
Introduced a log table to manage file entries and enable parallel ingestion, resolving Glue job failures due to duplicate inserts.
Business Outcomes
Driving Measurable Improvements in Data Quality and Performance.
Automating the ETL pipeline and embedding QA checks at every stage delivered measurable improvements in reliability, scalability, and data trust.
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Exathought’s solution delivered:
These results are modeled projections based on observed improvements in job success rates, ingestion timeliness, and QA coverage. Future phases will focus on extending the framework to additional data domains and environments.
Business impact
The automated ETL framework improved data accuracy, eliminated manual monitoring, and ensured faster, more reliable processing. With real-time alerts, organized job scheduling, and scalable ingestion, the client now operates with higher data trust, reduced failures, and quicker issue resolution across their pipelines.
Ready to modernize your data pipelines?
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Explore our expertise in Data & AI, DevSecOps, Software Reliability, and ETL Automation to unlock operational efficiency and data confidence.
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https://www.exathought.com or reach out to us at connect@exathought.com