End-to-end DW/BI, Data Lake & MDM managed services for a tier-1 European Airline

Goal of the Project

Our client was looking to develop data platforms and provide a single view of customer via data-driven applications. They embarked on a journey to consolidate existing siloed data platforms into an integrated data lake on AWS with the following objectives:

• Enable cloud-first strategy and leverage modern data architectures 
• Re-design existing data platforms to cater to current business needs 
• Reduce technical debt and standardize on fewer tools/technologies 
• Centralize data governance and enable single source of truth
  
  

Our Solution

Coforge developed multiple data platforms in the following domains to enable single version of truth and real-time data-driven customer-centric applications: 

• Commercial - comprising of customer data marts, marketing analytics and revenue management, revenue accounting, ancillary revenues 
• Operations - comprising of Crew Management, Flight Operations, Baggage, Cargo, Inventory 
• Advanced analytics - comprising of Route Econometrics, Booking Algorithms 
• Customer Master Data Management 

Coforge developed an end to end data platform using the overall architecture of the platform along with the tools as shown below: 

• Data Warehouse: Exadata, DB2, MySQL 
• Data Integration/ETL: Oracle Data Integrator, DataStage, PL/SQL 
• Data Quality: Trillium 
• MDM: Informatica 
• Data Visualization: OBIEE, QlikView, Tableau, Hyperion 
• Data Science: SAS 
  
  

The following diagram shows the MDM specific architecture. Here MDM is integrated with Salesforce CRM/Marketing cloud. 

Value Delivered to Client

• 40% of increment on identified unique customers through the consolidation of all the passenger’s interaction in a single platform. This has enabled more focused and specialized marketing actions with a positive impact of 3% on look to book ratio. 
• This bigger personalization of the offer has enabled a sustained increment on direct channels selling to reach almost 50% of total revenues. 
• Reduction of 25% on running cost thanks to the consolidation in a single platform, technology stack and support team. The progressive decommission of old applications allows to foresee an additional 5% on cost reduction YoY. 
• Time to market: reduced processing times from 4 months to 7 days 
• Earlier decisions can be taken and anticipate to the customer needs on disruption scenarios, as example, there has been a 3pp increment on NPS during last year.  
• Enhanced framework for data quality and data governance, which has allowed implementation of a centralized data platform.