Enterprise Data Warehouse
Unleashing Pharma Data Processing Excellence: A Serverless Transformation Journey
Situation
Exelixis: A prominent company in the pharma industry confronted substantial challenges related to their existing data processing infrastructure. These challenges included sluggish data integration from diverse sources, inefficient file processing due to manual involvement, and a lack of immediate action capabilities. The utilization of a PostgreSQL database for data warehousing led to the absence of essential features. Additionally, complex data-stewarding actions were impeded by the absence of an operational user interface, and the tracking of job statuses and errors was a convoluted process.
Approach
To overcome these obstacles, the organization undertook a comprehensive transformation of their data processing ecosystem, adopting a serverless architecture as the foundational framework. The serverless architecture was selected for its inherent scalability and flexibility, facilitating swift releases and adaptability to evolving processing demands. The architecture allowed for streamlined integration with a diverse array of data sources, addressing the delays caused by protracted integration processes. By incorporating event-driven triggers and parallel processing, the company achieved near real-time data processing, ensuring data availability precisely when needed. The introduction of a robust operational user interface facilitated swift and efficient data-stewarding actions. Furthermore, the architecture’s ability to sequence intricate data-management tasks enhanced automation and expedited data processing.
Outcomes
The implementation of the serverless data lake architecture yielded significant enhancements in the organization’s data processing operations. The automation-driven approach led to accelerated end-to-end data processing, significantly mitigating the need for manual interventions and resulting in seamless data flow across the processing pipeline. Swift and painless integration with a wide spectrum of data sources eradicated the challenges stemming from sluggish integration processes. The adoption of a serverless architecture (AWS Lambda) not only enhanced performance but also brought about cost efficiencies. Resource allocation optimization within this architecture translated to notable cost reductions. The integration of a user-friendly operational interface streamlined data-stewarding actions, allowing for prompt decision making and a marked reduction in delays linked to manual processing. The integrated monitoring system provided improved oversight, allowing for seamless tracking of job statuses and swift identification of errors. This proactive approach to error management substantially bolstered operational reliability.