Data Lake and Analytics for TREAD “Early Warning Reporting” to NHTSA

At a glance

We Re-Engineered the TREAD “Early Warning Reporting” (EWR) application architecture to transition from a mixture of siloed tools and applications to a robust integrated architecture that was also scalable to adapt to changing NHTSA regulations and achieve key Business and IT Goals

What we did

  • Digital Transformation
  • “RE-Engineer by Rewriting” Approach to Legacy Modernization
  • Data Lake Implementation and Data Analytics
  • Data Migration and Traceability
  • Enhanced Customer Experience
  • Framework Powered Test Automation
  • Continuous Development, Integration, Testing & Deployment
  • AGILE and DevOps based Delivery

TREAD Early Warning Report To NHTSA

In 2000, Congress passed the Transportation Recall Enhancement, Accountability and Documentation Act (TREAD Act) in response to fatalities related to vehicle accidents. TREAD “Early Warning Reporting” requires vehicle manufactures to report to NHTSA the Quarterly information related to Light Duty and Medium/Heavy Duty vehicles, Death & Injury, Production, Consumer Complaints, Property Damages, Warranty Claims and Field Report Counts.

 

Our client, a leading automobile OEM, had data and application related constraints in generating and publishing an acceptable TREAD “Early Warning Report” within their business process. These constraints were predominantly related to Missing critical external source system data, Invalid and Dirty inputs, Lack of Data Validation mechanism, Data Duplication and Discrepancies, Use of Desktop Applications leading to manual and tedious data mappings, Manual report generation in NHTSA format, Manual Review process, Manual report submission to NHTSA and No feed to data lake, thereby limiting Analytics capability.

 

We Re-Engineered the TREAD EWR application architecture to transition from a mixture of siloed tools and applications to a robust integrated architecture that was also scalable to adapt to changing regulations and achieve key Business and IT Goals.

 

Our solution facilitated Accurate and Timely reporting aligning with NHTSA regulation requirements and End-to-End transaction traceability with built-in capability to remove data inaccuracies and redundancies. The reconciliation of captured data changes were automated. Framework driven Archival process was implemented to meet data retention standards. A state of the art web application was designed and implemented to review and resolve data issues. Utilities were provided to download and analyze generated reports prior to NHTSA submission. The solution implemented was in alignment with organizational IT strategy on Cloud readiness.

 

Our solution was Cloud agnostic and securely streamlined the data ingestion from source systems. Regression Testing was automated by leveraging proven Test Automation frameworks and in-built accelerators, thereby negating manual intervention during continuous testing.

 

We delivered this solution leveraging a well-defined iterative AGILE and DevOps driven project delivery approach. We completed the activities and deliverables for this project well within the estimated schedule and cost.

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