Time is money, no more so than in the financial services sector where the ability to go from insight to execution can mean millions. The increased volume and variety of market data, however, mean that the right data analytics infrastructure is needed to ensure that PoC analyses can scale out to production and run in useful time. Our Client had developed a new bond default predictive model incorporating multiple datasets and millions of records, and needed to bring the solution to market quickly.
Analytics Engines architected a scalable infrastructure solution with XDP—its enterprise data backbone. XDP utilizes software defined infrastructure to configure and manage analytics services. Big data technologies were used to streamline data ingestion and provide a scalable compute environment for our client’s algorithms; the SaaS application tier was also configured in XDP. The solution went to production within 6 weeks, and was deployed on enterprise level within 5 months.
Our Client was able to deploy new infrastructure to handle the diverse data of its new model in record time. It is utilizing XDP to run its algorithms on a nightly basis, dynamically scaling out cloud compute resources to handle peak processing. As new models are developed, they can be deployed through reusable industrialized pipelines, further shortening the time from insight to execution.