Abstract
To understand the variables affecting Pakistan's cotton output, our research paper study focuses on applying the PowerBI tool to analyze data related to the cotton crop. We gathered data from two fields in Rahimyar Khan and Shah Alam Shah, Matiari, Sindh, to analyze the soil moisture content, availability of fertilizer, and environmental factors to improve agricultural practices and increase crop yields. The dataset contains data from monitoring dates and factors like temperature, humidity, soil moisture content, and signal intensity. We forecast cotton crop output, improve planting schedules, and foresee possible issues like bug outbreaks using predictive analytics. The study offers practical suggestions for decision-making procedures about fertilizer application schedules, irrigation schedules, and the sustainability of cotton crops. Limitations include data quality and scalability challenges, and future research will focus on improving agricultural techniques for better cotton growing.
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