Project 2 - Gender Bias in Science and Technical field

Gender Bias in Science and Technology: A Data-Driven Analysis As a data analyst with a background in digital marketing and a passion for leveraging data to drive meaningful change, I have explored the issue of gender bias in science and technology through a data-driven lens. This project focuses on analyzing and understanding gender disparities in STEM fields, providing actionable insights for policymakers, educators, and organizations committed to fostering diversity and inclusion.

The primary goal of this project was to import, clean, process, and analyze alumni data from multiple colleges. The project involved setting up a MySQL database, importing CSV files, cleaning the data, creating views, defining procedures for data transformation, and performing analytical queries to derive insights into alumni career choices.

Project: Analyzing Education Trends in Tamil Nadu Using Tableau Overview:This project explores education trends in Tamil Nadu, focusing on enrollment rates, educational attainment, gender disparities, and career choices, particularly in STEM fields. Using Tableau, we employ data visualization techniques to uncover insights

"EngLib Manager" is a dynamic Python project combining two essential tools: an English Dictionary App and a Library Book Management System. This multifaceted application serves both language enthusiasts and librarians alike. The English Dictionary App offers users comprehensive word definitions, synonyms, antonyms, and examples, empowering language exploration and learning. Simultaneously, the Library Book Management System provides librarians with an efficient platform to organize, categorize, and track library inventory, streamlining operations and enhancing user experience. Through intuitive interfaces and robust functionalities, "EngLib Manager" facilitates seamless access to linguistic resources and efficient library management, catering to diverse user needs in the digital age

EcomQueryPro" is a comprehensive project designed to delve deep into user data within the ecommerce domain. By importing and analyzing a dataset encompassing user behaviors and attributes, the project aims to extract valuable insights crucial for optimizing business strategies. Leveraging SQL commands and data manipulation techniques, it explores various dimensions such as user demographics, preferences, platform usage, and transactional patterns. Through a series of structured queries, it addresses key questions ranging from user engagement metrics to market segmentation, empowering stakeholders to make informed decisions. With its focus on data-driven decision-making, "EcomQueryPro" serves as a vital tool for enhancing operational efficiency and driving growth within the ecommerce landscape.

"VehInsight" is a Python project dedicated to Exploratory Data Analysis (EDA) on Vehicle Insurance Customer Data. This project aims to unravel insightful patterns and trends within the dataset, offering valuable insights for insurance companies. Through data visualization techniques and statistical analysis, "VehInsight" delves into various aspects such as customer demographics, policy attributes, claim histories, and risk profiles. By uncovering correlations, anomalies, and predictive indicators, it equips insurers with the knowledge needed to optimize pricing strategies, tailor marketing campaigns, and enhance customer satisfaction. With its focus on data-driven decision-making, "VehInsight" empowers insurance professionals to navigate the complexities of the industry and drive sustainable growth.