Scalable Data Solutions with APIs, Cloud Pipelines, and Predictive Analytics
Abstract
The mere growth of enterprise data necessitates dynamic functioning of scalable real time processes to achieve intelligent decision making. This work has a fresh architecture of integrated system based on Application Programming Interfaces (APIs), cloud-native data pipelines, and predictional analytics capable of streaming data volumes of great magnitude that is heterogeneous. Through API, it is reasonably simple to ingest data across distributed sources and serverless cloud pipelines make it simple to process data at scale in milliseconds regardless of workload levels. One application of a predictive analytics model which is deployed in this architecture is high-fidelity real-time forecasting, which allows business to optimise operations in real-time. This system was proven on a simulated retail store of 200 stores and 10 million transactions per day with constant transaction throughput (25,000 TPS), model accuracy of 94%, and savings of 30% compared to traditional infrastructure.