26% of major defects were detected due to well-defined strategy. This ensured that the program’s aim of ensuring around 85% accuracy for prediction was achieved
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Raw data from the sensors placed in the locomotive engines were fed into the ML algorithm/model to detect faults and issues and predict the warranty claims in advance. Infosys Advanced Analytics Program validated this model and made sure the predictions were accurate.
From a ‘no validation program’, the QA strategy has helped to bring a robust validation system to the client’s data analytics landscape.
- Infosys implemented a well-defined QA strategy to authenticate the analytics models
- Team built customized automation solution to speed up execution in one-week sprint duration
- QA validation strategy helped in identifying core defects. ~26% of major defects were detected due to well-defined strategy. This ensured that the program’s aim of ensuring around 85% accuracy for prediction was achieved
Strong knowledge of niche technologies
Infosys’ strong knowledge of niche technologies like ML Algorithm-Weibull, Occurrence Monitoring, SubPopulation, and the QA skills helped in end-to-end exhaustive validation.
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