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Context-aware, real-time and Self-Serve Bigdata Analytics

July 8, 2015

A leading software industry has minimized the data storage cost by 60 %. Our effective strategy enabled them to move loads of data to Hadoop clusters, thus assisted them to optimize the data and increase the processing speed.

Challenges

  • Insufficient capacity in old system to meet demand of over 20 million daily passengers
  • System crashes and slow system performance during peak demand that exceeded 40,000 concurrent users
  • Frustrating and cumbersome experience for customers trying to purchase tickets forced many to buy in person rather than electronically

Solution

  • Pivotal GemFire

Key Benefits

  • Support more than 200,000 concurrent purchases without impacting system performance
  • Provides the stable performance to book approximately 150,000 tickets per hour, compared to 60,000 in the old system
  • Transformed customer experience – reservation transactions complete in seconds, instead of 15 minutes
  • Shifted online purchasing from 50% of tickets sold to 65%, boosting revenue generated from e-ticket sales to INR600 million daily

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