Data infrastructure modernization reduces cloud costs by 50%Data infrastructure modernization on AWS delivers timely and accurate credit scores for a leading Fintech company
The customer is a global provider of commercial data, analytics, and insights on businesses. They offer services such as business credit scores and ratings to assess a company's creditworthiness and financial stability based on payment history, financial statements, and industry risk. They processed global trade data for 15 million customers from 800 different sources to calculate these credit scores. However, due to the legacy on-premise systems running on mainframe and Cloudera, data processing was slow and inefficient, ultimately hampering their ability to provide timely and accurate credit scores.
Sigmoid's AWS-endorsed partnership empowered us to revolutionize our customer's data engineering landscape. We crafted an intricate migration strategy, deeply comprehending their existing system and requirements. Agile methodologies, harnessing AWS technologies, steered our sprint planning and daily operations via Jira, fostering a collaborative, iterative development ethos. We instituted a scheduling and orchestration framework, employing AWS Step Functions for seamless data process coordination. The integration of AWS SNS event notifications fortified real-time updates, amplifying system responsiveness. This transformation hinged on an event-driven, notification-based architecture, elevating efficiency and responsiveness.
Sigmoid's transformational solution modernized our client's data engineering operations, substantially reducing costs and enhancing process efficiency. We ensured a seamless transition from a legacy system to a cloud-based infrastructure which bolstered reliability, streamlined maintenance, and empowered innovation through an agile tech stack.
savings in maintenance costs
reduction in data processing time
high availability and reliability