Historical sales data for 45 Walmart stores located in different regions are available. There are certain events and holidays which impact sales on each day. The business is facing a challenge due to unforeseen demands and runs out of stock some times, due to inappropriate machine learning algorithm. Walmart would like to predict the sales and demand accurately. An ideal ML algorithm will predict demand accurately and ingest factors like economic conditions including CPI, Unemployment Index, etc. The objective is to determine the factors affecting the sales and to analyze the impact of markdowns around holidays on the sales.

This project aims to analyze the data of an online retail store to gain valuable insights into customer behavior, sales trends, and operational efficiency. By leveraging data analysis techniques, the online retail store can make data-driven decisions to optimize marketing strategies, improve customer experience, and enhance overall business performance. Analyzed customer purchasing patterns in an online retail store. Identified valuable insights and purchasing behavior segments to aid the retailer in understanding customer preferences. Devised actionable strategies for enhancing sales and marketing efforts based on the insights gained

This project focuses on developing an interactive dashboard using Power BI to track and analyze sales data. The dashboard will provide an intuitive and visually appealing interface for users to explore sales trends, customer behavior, product performance, and other relevant metrics. By leveraging the capabilities of Power BI, the project aims to empower decision-makers with actionable insights for optimizing sales strategies and improving business performance.

This project focuses on analyzing COVID-19 data using SQL to gain insights into the spread of the virus, track its impact on various regions, and explore patterns and trends over time. By leveraging SQL's querying capabilities, data manipulation, and aggregation functions, we can extract meaningful information from the available COVID-19 datasets. The dataset contains details of cases, deaths, and vaccinations. This analysis is based on real data about covid 19 from March 2020 to July 2021 using MS SQL.