Projects
Here are some of my data analysis projects, where I leverage Excel, Python, SQL and
Tableau to uncover insights, visualize trends, and drive data-driven decisions. Each project showcases my ability to clean, analyze, and interpret data to solve real-world problems
Objective: Analyze sales data to uncover trends in revenue, customer behavior, and product profitability using dynamic Excel dashboards.
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Techniques Used: Data cleaning, transformation, relationship modeling, and interactive data visualization.
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Tools/Libraries: Excel, Power Query, Power Pivot, DAX.
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Impact: Delivered actionable insights to optimize sales strategies, enhance pricing decisions, and improve customer targeting.
Objective: Analyze hospital patient data to uncover trends in disease prevalence, treatment outcomes, and operational patterns to optimize resource allocation.
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Techniques Used: Data preprocessing, exploratory data analysis (EDA),Feature Engineering
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Tools/Libraries: Python,Pandas, Matplotlib, Seaborn.
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Impact: Identified key insights such as disease prevalence, stay duration, and treatment outcomes, which can guide hospitals in improving patient care, optimizing resource management, and addressing public health issues.
Objective: Investigate declining customer engagement and conversion rates at ShopEasy by analyzing campaign performance, customer reviews, and behavioral data to identify areas for marketing optimization.
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Techniques Used: Data cleaning, feature engineering, sentiment analysis, conversion funnel assessment, and interactive data visualization.
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Tools/Libraries: MySQL, Python (NLTK, pandas), Power BI,Powerpoint.
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Impact: Delivered insights into campaign effectiveness, content engagement, and customer sentiment—informing strategies to boost ROI, enhance user experience, and increase conversions.
