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A large brewer decodes social media with Infosys

Author: Surya Prakash G., Delivery Manager, Infosys Validation Solutions

Digitization has become the buzzword in every industry vertical, as end consumers have been swept away by the digital world. The advent of Internet of Things (IoT) implies that smart products, services, factories, and operations are replacing traditional ones. Data from social media is enhancing decision making to increase revenues by impacting unstructured data for analysis. This is leading to an exponential increase in data analysis, interpretation, and the way data from social media is used in a meaningful form. With this, the focus on data testing has to move beyond volume and variety, to include velocity and veracity of data.

Recently, Infosys validated data from social media channels, by using the Infosys 4D++ framework to achieve faster time to market and also reduce cost for a global brewing client.

This client, a leading beverage and brewing company, generates over US$1 billion annually in revenue and selling more than 200 brands. It has offices across 24 countries and has a 25 percent global market share. We partnered with the client to enhance its focus on enriching relationships with customers and the communities. Our big data implementation enhanced customer data by using third party feeds collected from social networking sites. Subsequently, enriched customer data helped in targeted campaigning and business expansion. The objective of this complex testing endeavor was to validate huge volumes of unstructured data coming from different social networking sites and verify data quality and reports.

The following lists some of the key components of our testing approach:

  • End-to-end testing to ensure successful consolidation and implementation of huge data coming from numerous sources
  • Setting up a stable testing environment
  • Robust functional and user interface (UI) testing including look and feel testing
  • Consolidation and validation of data from multiple sources which are in different formats

To solve these challenges, Infosys came out with an approach to validate 100 percent of the data by testing at each conversion stage that covers all data permutations with automated tools. Also, end to end data validation was covered right from data ingestion to data visualization (including mobile validation). Data validation was performed using automated utilities developed for different stages of data conversions.

Here are the key benefits of our solution:

  • Reduction of cost of quality (COQ) by 10-15 percent through early detection of data issues at source during data ingestion
  • 15 percent reduction due to automated data validation by using utilities at various stages
  • 100 percent test coverage through automated approach for validation of all scenarios
  • Time optimization using query repository

We would love to discuss this and many other such exciting implementations on Big Data testing with you. Infosys is a Silver sponsor of HPE Discover 2016. Do drop in at Booth #134 for a quick chat. More information on our participation is here.

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