A global agricultural equipment manufacturer providing after-sales warranty for agricultural equipment sought to modernize its data ecosystem for data analysis and monetization.
Infosys partnered with the company and its dealer network across the US to harvest data for advanced analytics.
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Business users access relevant data for an objective assessment of risks to generate comprehensive warranty policies
Infosys expanded the sources of data to gain visibility into the equipment lifecycle. The existing system tracked data only during the warranty period. Infosys extracted more than 75 million records from equipment data during warranty and extended coverage as well as maintenance / service records of dealers.
Our team leveraged Spring XD and Python for data transfer and batch processing of exported data. We used Informatica ETL products and IBM Netezza data warehouse appliance to optimize the data system.
Several software frameworks ingested and processed the volume of data, including Hadoop Distributed File System (HDFS), Apache Crunch, Hadoop MapReduce, Apache Hive, Sqoop, and the Oozie workflow scheduler system. Java DOM Parser, XSLT, and XSD were used to manage and store documents.
The technology stack created a scalable big data system for real-time data capture, ingestion, and analytics. It integrated product, warranty, telematics, customer, and dealer data. Live data from the ecosystem flows into the Hadoop data lake and data mart environment that stores historical records.
Infosys’ system processes an average of 400,000+ records every day, including post-warranty repair / maintenance orders and over-the-counter sales of spare parts.
Our big data solution provides real-time visibility across inventory and powers concurrent analytical processes.