SYSTEMS AND METHODS FOR INTEGRATING BUSINESS PERCEPTIONS IN REAL TIME

Abstract

This paper describes computerized systems and methods for integrating real-time insights among various entities involved in distribution processes. The system includes a real-time data mesh module for ingesting and harmonizing data from multiple sources, a data lake for storing harmonized data, and an advanced analytics and machine learning (AAML) module for generating insights using predictive analytics, anomaly detection, and recommendation engines. A single-pane-of-glass user interface (SPoG UI) provides visualizations of these insights through interactive dashboards. The system supports customer, supplier, reseller, and partner systems, enabling efficient data sharing and synchronization.It uses natural language processing (NLP) for sentiment analysis, topic modeling for identifying key themes, and clustering algorithms for customer segmentation. Continuous learning mechanisms ensure the system adapts to new data in real time, improving decision-making and operational efficiency.