Project : Service IntelligenceSI measures Performance, Availability, Reliability and Quality for all Digital Experience Technologyonline applications to improve user experience(UX) and application health by instrumenting, monitoringand reporting metrics for online applications within DET using Big Data and DWH technologies.▪ Strategized and developed e-commerce application User Event and server log data processingusing Splunk, Sqoop, Flume, Informatica, Unix shell and NLP using Python NLTK.▪ Prepared data models to build data marts in Oracle 11g database by migrating legacy jobs toimprove maintainability and performance.▪ Analyzed high-volume consumer order, defects, page performance and campaign tracking usingPig and Hive, and created dashboards on Tableau to monitor health of applications.▪ A key member in building an APM solution in J2EE platform on Dynatrace and Tealeaf datawhich reduced cost by ~$2 million over a year while CSAT score improved to 76% from 52%.▪ Developed near real-time report using Splunk by parsing machine logs from Microservices, withKafka as middle-ware streaming system and utilized embedded Machine Learning tool (MLTK).▪ Integrated Clickstream from Vertica and Netezza databases by developing Informatica ETLworkflows to produce key metrics and perform ad-hoc analysis using Business Object.▪ Introduced and led automation defect reporting being an SME and sole developer for the effort.

Project : Intelligent Test CellClient : GE AviationSummary:This project aims to reduce the cost of aircraft engine overhaul by certifying them based on test results from various test cells. Test data of engine components are processed to data mart through complex business rules, data quality and standardization steps. Service Engineers at test cells do the performance review of all the aviation engine components released from the shop floor. This review is aimed at assessing the overall efficiency and performance of the engine components. Intelligence Test Cell tool allows the business to be proactive and take necessary steps before the component is released from the floor instead of doing complete overhaul all the time.

Project : Aviation Pull InClient : GE AviationSummary : The objective of this project is to store LRU ( Line Replaceable Unit ) reliability data of avionic components from various FRACA( failure reporting, analysis and corrective action) systems and XFRACAS systems. A multi-data interface tool , accessed by external and internal users, uses the data to monitor product reliability.

Project: GRID (Global Repairs Information Delivery) GE Repairs Business implements SAP solutions to manage the Global Repair Business operating in 60locations across 13 countries.GRID Data Warehouse accommodates and manages source data from ERP systems, suchas SAP, COMPAS, JDE, CS DW, MS Access, MS Excel etc. with more than 500+ Informaticamappings and 130+ Cognos reports, 20+ Tableau Reports & Dashboards.▪ Prepared project plans, coordinated implementation between onshore and offshore.▪ Developed Informatica Mappings to extract data from different sources like SAP IDOC, SAPABAP Tables, SQL Server, Oracle, Flat FILES, and KRONOS using Power Exchange.▪ Provided support and consulting activities to source and downstream ERP teams while integratingsource servers to ensure error free dataflow E2E.▪ Testing - conducting SIT, UAT and getting sign off on new solutions.▪ Supporting - production migration activities and post-production validation.