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

AdfarTech 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

AdfarTech 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.
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