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This repository showcases my skills and experience in the field of data analysis. Here, you will find a collection of projects and analyses that demonstrate my ability to extract insights and make data-driven decisions.
Welcome to my Data Analysis Portfolio! This repository showcases my skills and experience in the field of data analysis. Here, you will find a collection of projects and analyses that demonstrate my ability to extract insights and make data-driven decisions.
In this project, I analyzed and visualized the sales data for Retail and Food Services in the U.S.A. The data is sourced from the U.S. government website and has been processed using SQL to create a database for easy management and analysis. The main focus of this project is to explore the sales data based on NAICS (North American Industry Classification System) code and category.
Superstore Sales with Streamlit is a data visualization and analysis project that uses the Streamlit framework to create an interactive web application for exploring and analyzing sales data from a superstore. This project aims to provide an easy-to-use interface for users to gain insights into sales trends, Sales performance, product performance, Shippin analysis and Location analysis.
The objective of this project is to build a sales forecasting model that predicts future sales for each Rossmann store. By leveraging historical sales data, store-specific information, and external factors like holidays, the model aims to provide reliable sales predictions for upcoming periods. This will help Rossmann allocate resources efficiently, optimize store operations, and maintain customer satisfaction by ensuring the availability of products.
his project aims to analyze the historical trends of Netflix stock prices using Python and data analysis techniques. By examining the stock price data, we can gain insights into price fluctuations, patterns, and potential trends, which can be valuable for investors and financial analysis.
This project revolves around the exploration and analysis of user engagement patterns on the popular social media platform, Instagram. By delving into user data and interaction metrics, this project aims to provide valuable insights into user behavior, content performance, and trends.
Pizza Sales Analysis has a comprehensive year's worth of sales data from a fictitious pizza place. The dataset includes detailed information about each order, such as the date and time of purchase, the types of pizzas served, their sizes, quantities, prices.
Exploring a treasure trove of insights and captivating visualizations drawn from a vast HR dataset covering 2000 to 2020, featuring over 22,000 records. Painstakingly curated and analyzed using PostgreSQL, this powerful dashboard showcases its findings through the elegance of Power BI. Unravel the secrets of the organization's workforce with answers to vital HR inquiries. Discover the gender and race/ethnicity breakdown, age distribution, headquarters vs. remote locations, average employment length for terminated employees, gender distribution across departments and job titles, job title distribution, highest turnover department, state-wise employee distribution, and changes in employee count over time based on hire and termination dates. Experience a profound understanding of employee tenures across departments. Employee-Distribution delivers valuable HR insights at your fingertips.
The project will cover a wide range of areas, including user engagement, sales performance, marketing effectiveness, and more. You'll be provided with access to datasets containing user information, events data, and email engagement details.
This project predicts the sales demand for various items in different stores based on historical sales data. The objective is to develop a machine learning model that can provide accurate forecasts for future sales of each store-item combination.
E-commerce companies are relentlessly working to augment user experiences and bolster sales by offering tailor-made product recommendations. The "E-commerce Product Recommendation" project endeavors to create a recommendation system that suggests products to users based on their historical interactions and preferences.
In this project, I am analyzing hiring process data to gain insights from about records of previous hires within a multinational company. By analyzing this data, I am aiming to uncover valuable trends and information about the company's hiring process, which can contribute to making informed decisions and improvements for the future.
The focus of this project is to delve into the realm of international debt analysis and understand its dynamics in a specific context. By narrowing down the scope, I aim to provide in-depth insights that resonate with the complexities and challenges faced by the selected region/country.
If you have any questions, feedback, or collaboration opportunities, please feel free to reach out to me. You can contact me via email at info@tushar-aggarwal.com or connect with me on LinkedIn at Tushar Aggarwal.
Thank you for visiting my Data Analysis Portfolio! I hope you find my projects informative and insightful.
Selected from shared topics, language and repository description—not editorial ratings.
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