Developed a comprehensive credit card weekly dashboard using Power BI that provides real-time insights into key performance metrics and trends, enabling stakeholders to monitor and analyze credit card operations effectively. 

Our model is designed to forecast interactions between unknown drug-protein pairs by transforming features of these pairs into a condensed latent representation and predicting the specific class of DPIs for those samples. 

Predicted start-up profits using regression algorithms and selected the best model based on historical data (R&D spend, administration costs, marketing spend, and state of operation) to set realistic goals and optimize strategies for better decision-making. 

Objective of this project is to leverage SQL analysis to extract actionable insights from the music store's sales, customer, and product data, enabling informed decision-making, improved customer satisfaction, and optimized business performance. 

The objective of this project is to help Vrinda Store develop a comprehensive annual sales report for 2022, enabling them to gain deeper insights into customer behavior, identify sales trends, and optimize business strategies for increased growth and profitability in 2023. 

This project performs Exploratory Data Analysis (EDA) on Diwali sales to uncover useful business insights from the dataset to help target the right audience and boost sales during the festive season.