Major US Airline
Centralizing data management and consumption and growing strategic data analytics leveraging AWS Lakehouse platform.
A leading U.S. airline partnered with Credera partnered and contributed to the design and implement of a modern data analytics platform that will bring in $10 million in cost saving in enterprise data infrastructure over the next 5 years.
At a Glance
A leading U.S. airline wanted to improve operational cost efficiencies while advancing analytics and improving resiliency, scalability, and reliability of its enterprise data platform. The client engaged Credera to design and implement a data lake house architecture from the ground up and create an analytics platform that would take advantage of AWS native cloud capabilities to improve data governance, accessibility, security, and traceability. This will result in a 30% reduction of data product time-to-market and cost saving of more than $10 million in the next 3 to 5 years.
Delivering a new data and technology architecture.
A leading U.S. airline was operating on a legacy technology footprint and wanted to provide a future-proof data architecture to democratize data. The organization was highly siloed with significant redundancies and inefficiencies in development, product usage, and data and knowledge sharing. Data roles and responsibilities were lacking, focusing on enforcement rather than value-add creation.
The client engaged Credera to assess the current state and provide future-state recommendations and roadmap to deliver a new architecture leveraging modern tooling on AWS and a DevOps solution on Gitlab. Key goals included increasing the accessibility of valuable enterprise data, improving the scalability and performance of the data platform, and enabling support for new enterprise data products and tooling.
Implementing an enterprise data warehouse using the AWS technology stack.
The leading U.S. airline and Credera co-developed a strategy for modernizing the data architecture using bounded contexts for key data concepts including, customer, schedule, equipment, technical operations, and others. The data platform architecture was similarly revamped using the latest AWS services, with the analytics platform shifting from a pure data warehouse to a modern data lake house on S3, Lake Formation and Redshift. New data patterns were defined for repeating key components of the data lake house within each data domain and cross-domain integration.
Once the new strategy was in place, Credera partnered with several of the client data teams to accelerate implementation. Credera helped assess, score, and select the right AWS tooling, and built reference implementations to demonstrate the proper usage of the new data patterns for client teams using AWS native services.
With self-service analytics being a key client expectation, Credera also developed new self-service patterns for analysts to access the S3 data lake and Redshift data warehouse using Alteryx and Tableau. This ensured that the standard tools of the business remained supported, with clear guidelines on how to leverage within the new cloud-based architecture.
Realizing the benefits of the modern data architecture.
This U.S. airline now has a modern data architecture on AWS and is working to modernize legacy data pipelines and products.
As a result of this initiative, the airline has experienced the following:
Identified millions of hours of efficiency gains over five years, driven by improved trust in data and collaboration across silos.
Delivered key pilot data products for TechOps, personnel, and customer to demonstrate value and accelerate adoption.
Provided the foundation for increased collaboration and standardization through common data integration and implementation patterns.
Improved data security posture without sacrificing accessibility for data consumers.
Consolidated technical metadata to improve discoverability and reduce time to onboard new data producers and consumers.
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