The client was facing challenges such as lacked integration capabilities, scalability issues that could not cater to the growing demands, and more. IGT with its extensive domain knowledge and technical expertise supported the client by modernizing its data platform which resulted in real-time intelligence insights, unstructured data integration in Big Data, scalability during peak hours, etc to help make effective business decisions.
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The airline wanted to modernize its data platform to resolve the challenges posed by the existing system. The new system should:
- refresh real-time / near-real time data for effective decision making.
- provide real-time intelligence by modernizing data architecture and infrastructure.
- provide unstructured data integration and analysis.
- support execution of complex resource intensive queries generally requested by business.
- support peak hour user work load by paying additional cost for peak workload window.
- 60% saving on infrastructure cost
- 4x improvement in processing time
- Zero licensing fee for software
- Integration of social media and survey data in EDW
- Real-time integration support in data architecture
The airline is a budgeted carrier in the Middle East, flying 70 million passengers to 95 destinations across Europe, Middle East and GCC, Africa, and Asia. The airline continues to expand its network with more regular flights, more direct routes and more comfortable inflight options.
The client’s existing data platform was an on-premise solution built using traditional tools and technologies. It had following challenges:
- Lacked Integration capabilities with other modules
- Legacy Data Architecture built with an intent of historical reporting
- Not scalable to cater the growing demands of platform’s data
- Huge licensing and infrastructure cost
The client selected IGT Solutions for its requirement for data platform modernization & reporting. IGT leveraged its extensive domain knowledge and technical expertise to implement a solution best-fitted to address the challenges. The modern version consists of the following:Cloud-based infrastructure to provide scalability during peak hours, performance improvement and cost saving on Data center, Software licensing and Appliances/ Servers.
- Cloudera Impala for EDW to support complex queries, massively parallel processing and vertical scaling based on the user workload and complex business logic.
- Kafka for real-time PNR data integration, so business operations can know the actual inventory positions and make effective decisions.
- Utilization of modern ETL best practices to uplift the existing data architecture and enable parallel processing.
- Unstructured data integration in Big Data, so businesses can perform social analytics, sentiment analysis, surveys and customer 360 analysis. Social media connectors, web scrappers, Python are utilized for the same.
- Complex ETL processing and business logics are coded in Map Reduce, Pig, and Hive to improve performance and resource utilization.
- Power BI and SSRS are applied for supreme data visualization
- Scoop is utilized for CDC processing. Scoop merged with data architecture best practices to refresh data near real-time.
Technology Stack in Scope