This study analyzes the potential of microgrid (MG), which combine renewable energy resources and supplies to provide sustainable and dedicated power solutions. Specifically, we utilized the source data from the TwInSolar Consortium and the University of La Reunion. Our examination required inspecting load and photovoltaic (PV) data, so we calculated the minimum and maximum average and visualized the correlation on Tableau. For data preprocessing tasks, we cleaned the data by removing unnecessary rows, merged the tables before transforming them into CSV format, and uploaded them onto Databricks file distribution system (DBFS). Then, they are processed by creating pipeline and ETL (extract, transformation and load) process. We manipulated and visualized the data using tools such as Power BI and Tableau. The analysis identifies the production of maximum and minimum PV, evaluates weather patterns' impact on production, and measures the quantity of the energy shortage between load demand and PV generation. This research shows the process of handling and analyzing data includes steps from data cleaning, conversion into CSV files, uploading to Databricks DBFS, transformation into Parquet files, connecting to SQL, and finally visualization in Tableau. In this study, we adopted a different approach by leveraging cloud infrastructure to perform the analytical tasks and conducted our visualizations using business intelligence (BI) tools.