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Building a Modern & Agile Data Platform across the Airline Value Chain for a Leading Middle Eastern Airline

Building a Modern & Agile Data Platform across the Airline Value Chain for a Leading Middle Eastern Airline

Business Challenge

Our client, a leading airline in the Middle East, aimed to transition their Big Data and Enterprise Data Warehouse to Azure cloud. This move would facilitate transformations, reporting, what-if analysis, customer intelligence, and ad-hoc analysis across various divisions - Operations, Customers, Cargo, and Shared Services (HR, Finance)

Coforge Solution

Coforge formulated a complete roadmap for a strategic shift from an on-premise data platform to a cloud-based data platform covering the complete data lifecycle from data assimilation to data analysis.

As part of the roadmap, we implemented migration to the Cloudera Data Platform (CDP), moving the on-premise Data Hub to the cloud. Real-time customer transaction data feeds into Kafka, with continuous data consumed by Spark Streaming code and converted to different layers. The transformed data was loaded into Snowflake for advanced analytics and report generation using Microstrategy.

This was accomplished by a team of approximately 70 individuals working in multiple Squads specializing in Hadoop, Spark, Scala, Python, Azure data services, Snowflake, Microstrategy, Power BI, and Data Testing to drive the engagement.

Results

  • The modernization of the data platform resulted in a 27% faster time to market and a 60% savings on the Data Analytics budget. Project roll-outs were improved by decentralizing execution and enabling department-wise Squads.
  • Working across Commercial, Operations, Enterprise Data, and Middleware domains, providing flexible team structure and augmenting Site Reliability and DevOps capabilities across e-commerce and Enterprise Data streams to improve monitoring and alerting, incident response and resolution, capacity planning, and performance optimization.

Key Highlights

  • Enabling business for self-service & advance analytics capabilities.
  • 27% faster time to market
  • 60% savings on Data Analytics budget and improved project roll-outs
  • Creation of specialized Squads to directly support multiple departments and enabled business teams.
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