AI-Driven Analytics on Oracle Cloud Infrastructure for Real-Time Business Intelligence

Abstract

As the demand to involve real-time decision making continues to rise, enterprises seek to adopt AI-powered analytics in order to capitalize on the power of big data and generate valuable information. The Oracle Cloud Infrastructure (OCI) offers a platform which is highly scalable in terms of AI-driven analytics, and thus, helps organizations mix machine learning models and sophisticated analytics smoothly with the cloud infrastructure. This paper will discuss how OCI can support real-time business intelligence (BI) by creating AI-based analytics. The model deals with the deployment of different services presented in Oracle Cloud (e.g., Oracle Autonomous Data Warehouse, Oracle AI, or Oracle Analytics Cloud) to facilitate the process of data-driven decision-making. The architecture proposal uses real-time data ingestion and processing and visualization capabilities, machine learning algorithms to provide predictive and prescriptive analytics. The framework enables automatic cleaning of data, detection of anomalies and optimization of business processes. Furthermore, it highlights how AI models are being implemented in OCI to improve data accuracy and reliability so that a business can respond to insights in real-time. Through the Oracle superior cloud-native services, organizations are able to increase the speed of their BI systems and remain to be scaled, secure, and cost effective. The challenges that are highlighted in the framework also include data governance, model training and performance monitoring with solutions that could be used to mitigate them. In general, this study illustrates the possibility of OCI to redefine the traditional business intelligence into a dynamic and AI-centered system that can provide real-time and action-oriented insights that can be used to make strategic business decisions.