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
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
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
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.