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In this project, I embarked on a financial self discovery journey utilizing Power BI as my compass. By analyzing data extracted from my student bank account, I crafted an interactive dashboard that shed light on my spending habits, budgeting effectiveness, and overall financial health. This illuminating experience empowered me to make informed decisions and take control of my financial future.
In this project, I embarked on a financial self discovery journey utilizing Power BI as my compass. By analyzing data extracted from my student bank account, I crafted an interactive dashboard that shed light on my spending habits, budgeting effectiveness, and overall financial health. This illuminating experience empowered me to make informed decisions and take control of my financial future.
In this project, I embarked on a journey to demystify the world of wealth by analyzing the prestigious Forbes Billionaires List. Leveraging the power of SQL and Power BI, I constructed an interactive dashboard that reveals fascinating insights peering beyond the surface to offer a deeper understanding of their journey to the top.
In this project, I built a full end-to-end data analytics solution to help a company understand and predict customer churn. Using SQL Server, Power BI, and Python, I designed a complete ETL pipeline that cleaned and transformed over 7,000 customer records, uncovering key patterns across demographics, service usage, and billing behaviour. The resulting interactive Power BI dashboard revealed that month-to-month contract holders and fiber optic users were the highest-risk segments, while competitor offers emerged as the number one reason customers left. Taking it further, I trained a Random Forest machine learning model with 80% accuracy to predict which new customers were likely to churn, feeding those predictions back into Power BI for a live churn prediction page. The project delivered five concrete business recommendations to reduce attrition and improve customer retention strategy.
In this project, I scraped, processed, and visualized key market insights by collecting real-time cryptocurrency data, including price trends, market capitalization, and trading volume, and storing it in a structured format.
To make sense of the data, I built dynamic visualizations using Python (Matplotlib & Seaborn), displaying key trends such as price fluctuations over time, market share distribution, and comparative analysis of top cryptocurrencies.
Additionally, I implemented an automated email reporting system, which sends the latest cryptocurrency insights, including key charts and findings, directly to the recipient’s inbox. The automation ensures that new data is fetched, analyzed, and visualized daily without manual intervention.
This project showcases my ability to work with data automation, web scraping, visualization, and automated reporting, transforming raw financial data into actionable insights for decision-making.
In this project, I embarked on financial analysis to gain valuable insights into the performance and growth of the business. This involved extracting key metrics from a CSV file and transforming them into a comprehensive, interactive dashboard using Power BI.
In this project, I conducted an HR analysis to gain insights into employee performance, job satisfaction, and promotion trends within the organization. This involved extracting key HR insights, such as employee tenure, job satisfaction levels, performance ratings, and departmental information, and transforming them into a detailed, interactive dashboard using Power BI to show the insights. The dashboard helped highlight areas for potential promotions, layoffs, and overall workforce trends.
In this project, I automated a repetitive reporting workflow that was costing analysts up to 30 minutes of manual effort per report cycle. Using Excel VBA and Microsoft Outlook, I built a system that automatically processes raw call center data, calculates performance metrics across 30-minute intervals, generates a clean formatted report, and emails it to the right stakeholders — all with a single button click. The result is a scalable automation system that transforms a tedious manual process into a reliable, repeatable workflow.
In this project, I transformed COVID-19 data (Jan 2020-present) into an interactive dashboard using web scraping with Power Query and Microsoft Excel. This project uncovers valuable trends and insights, empowering informed decision-making and a clearer understanding of the pandemic's impact.
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