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The Real-Time Revenue and Expenditure Analysis project aims to analyze and visualize financial data related to budgets across different departments or ministries. This tool allows users to input specific departments to focus on and provides visual representations of the data through bar charts and pie charts.
A data-driven A/B testing project comparing website performance under Light and Dark themes. Analyzes user engagement metrics using statistical tests, correlation analysis, and predictive modeling to identify behavioral patterns and theme effectiveness. Built in Python using Jupyter Notebook with pandas, seaborn, and scikit-learn.
An in-depth analysis of customer acquisition cost (CAC) across marketing channels in 2023, using Python for data processing and visualization. The project evaluates performance metrics like CAC, conversion efficiency, and spend effectiveness to inform marketing strategy and budget optimization.
Comprehensive data analysis project exploring Netflix’s 2023 viewership trends to uncover insights on content performance, audience preferences, and seasonal patterns. Built using Python with pandas, matplotlib, and seaborn to guide smarter content strategy decisions based on data.