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Independent testing and validation of a utility management system

the story

The client is a global energy and sustainability management company. By leveraging an extensive data warehouse, the client provides technology optimized solutions for saving resources. Given the complexity and high volume (1 terabyte) of data, the client's proprietary energy management software required in-depth verification at various levels. Nagarro was selected to independently test and validate the new system and ensure zero loss to business. We successfully delivered independent, comprehensive testing with 100% functional coverage.

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challenge

Owing to the complexity and high volume (1 terabyte) of data, the client's proprietary energy management software required in-depth verification at various levels. Further, their advanced segmentation solution and rapid energy modelling required rigorous testing for accurate analysis.

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process

We set up a team of testers to articulate a strategy for seamless ETL transformation and BI report testing with minimum defects and maximum coverage of data scenarios.

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solution

We successfully provided independent and comprehensive testing with 100% functional coverage and reduced the regression cycle with automated ETL testing. Further, the centralized team ensured optimal resource utilization that lead to measurable cost savings.

Team Nagarro received appreciation from the client for their knowledge and experience in ETL testing. Our strong ETL testing capabilities helped combat the critical data transformation challenges, which were adversely affecting the data integrity related to utilities consumption across millions of households. After performing independent testing and validation, a near zero defect and superior quality energy management software was successfully delivered to the client.

Engagement QA Director

Nagarro

read the full story

Nagarro was selected to independently test and validate the new system and ensure zero loss to the business. We articulated a strategy to minimize defects and maximize coverage of data scenarios.

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