
AI & E-Commerce Analytics Projects
Notes: These projects reflect my passion for integrating AI, data, and actionable insights to solve real-world business challenges. From developing AI-powered healthcare applications to designing predictive analytics platforms for retail, I focus on building practical, user-centered solutions that deliver measurable results. I am dedicated to innovation, data-driven problem-solving, and transforming complex challenges into intuitive, ethical, and effective outcomes — using only synthetic or publicly available data.

The Power BI project dedicated to Adidas sales analysis provides an in-depth look at the company's performance across the United States, leveraging advanced data visualization tools to offer valuable insights. This dynamic dashboard features a range of visualizations to depict sales trends by month, state, region, product, and retailer, allowing users to view data from multiple perspectives. With key performance indicators and detailed analyses, the dashboard helps users understand and leverage sales trends effectively. Interactive features such as slicers and filters enable users to drill down into specific data points and tailor their analysis to meet their needs.
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Discover the power of data analytics with our comprehensive Power BI dashboard tailored for Blinkit's grocery sales. This dynamic dashboard offers a holistic view of business performance through meticulously crafted visualizations and key metrics. It captures essential metrics such as total sales, average sales, number of items sold, and average customer ratings, providing critical insights to evaluate overall performance and identify areas for improvement.


This Power BI dashboard provides a comprehensive analysis of employee data through dynamic visualizations such as heat maps, bar charts, donut charts, and matrix charts. It highlights key performance indicators (KPIs) like attrition rates, active employee counts, and job satisfaction levels, offering HR managers clear insights to support data-driven decision-making. The matrix chart, in particular, effectively displays job satisfaction ratings, enabling HR teams to better interpret employee feedback and trends.
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The Netflix dashboard in Tableau provides a powerful platform to visualize and analyze data on movies and TV shows, offering insights into content trends, regional availability, and viewer preferences. By plotting the number of movies and TV shows added over time using line charts or area graphs, we can uncover growth patterns in Netflix's content library. This analysis helps identify periods of accelerated expansion or slowdowns, which may correlate with marketing campaigns, strategic shifts, or external events. Additionally, temporal analysis can reveal user engagement patterns, such as spikes in activity following new releases or seasonal trends.
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