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- Designed a database schema with 8 critical retail data fields.
- Achieved 95% accuracy in cleaning, filtering, and calculating transaction revenue.
- Analyzed customer behavior and revenue trends using cohort identification and pivot tables, covering around 23,000 transactions.
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- Deployed interactive dashboards to track key health insurance metrics, reducing report generation time by 40%.
- Evaluated claims data to identify cost-saving opportunities, saving the company 15% in operational costs.
- Visualized provider performance and network utilization for strategic decisions, improving network efficiency by 20%.
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- Investigated market trends in multiple European cities using Excel, identifying opportunities to increase occupancy rates by 12%.
- Illustrated booking patterns and average prices, highlighting room types and host demographics, leading to a 15% increase in revenue for top-performing hosts.
- Uncovered customer satisfaction trends to inform market strategies, resulting in a 10% improvement in customer reviews.
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- Processed 2823 unique sales transactions from the dataset.
- Employed RFM analysis to categorize customers into 7 distinct segments.
- Identified November 2004 as the peak sales month, driven primarily by Classic Cars.
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- Extracted insights from sales data, optimizing operations and increasing efficiency by 25%.
- Supported sustainable growth through data-driven decisions, contributing to a 10% revenue increase.
- Developed and implemented dynamic pricing models based on sales trends analysis, resulting in a 15% increase in average order value.
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- Created data-driven HR dashboards, reducing recruitment cycle time by 20% and improving hiring quality by 10%.
- Examined attrition, demographics, turnover, and wellness trends, providing insights that improved employee retention rates by 15%.
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- Achieved 99% accuracy in predicting heart disease.
- Enhanced prediction accuracy by 20% and reduced processing time by 30%.
- Implemented the model in real-world applications, impacting care decisions for over 1,000 patients annually.
- Researched factors impacting diabetes prevalence to support targeted health interventions, leading to a 20% increase in awareness programs.
- Explored demographics, lifestyle, and environmental contributors, shaping effective strategies that reduced diabetes rates by 10% in the region.
- Formulated tailored public health initiatives to address and reduce diabetes rates, reaching over 5,000 residents.
