The project "Kaiture-Agriculture-Business-Reports-with-Power-BI" focuses on utilizing Business Intelligence to optimize agricultural yield and productivity. By integrating Power BI for data analysis, this project provides comprehensive insights into crop production patterns, market trends, and key factors affecting yield. It applies various analytics methods, including descriptive, diagnostic, predictive, and prescriptive analytics, to improve decision-making processes within Kaiture. Additionally, the use of machine learning models like Decision Tree, Gradient Boosting, and Random Forest enhances prediction accuracy, ultimately helping the company develop sustainable and data-driven strategies for improving agricultural productivity.
