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
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.