Projects
A collection of my top data analysis projects, including data visualization, SQL, Tableau, Power BI, and Excel-based work, showcasing my ability to analyze complex datasets, generate insightful visualizations, and apply SQL queries for data manipulation. These projects demonstrate my proficiency in tools like Python, R, SQL, and Excel for data-driven decision-making.
British Airways review (Tableau)
British Airways, one of the great airlines, or is it?
Ever wondered if a big airline’s reputation matches real passenger experience?
I dove into thousands of public reviews to break it down, cutting through the hype with data and Tableau.
What I set out to solve:
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Track how British Airways’ customer ratings have shifted over time
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Pinpoint which countries (and aircraft types) get strong reviews or rough ones
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Compare detailed metrics like cabin staff service, food, and seat comfort, not just the overall score
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Make it easy for travelers, airline staff, and analysts to see strengths, spot problems, and make better decisions
Filters : traveler type, seat class, aircraft model, and date range, enabling granular insights.
Identified low-rated services and geographic trends, helping airlines improve customer experience and operational decisions.​
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Company Hiring Trends 2025 Dashboard (Power BI, DAX)
Tired of the guesswork in job searching, I scraped thousands of LinkedIn job postings (title, company, location, remote/hybrid/onsite, and full descriptions) and built a Power BI dashboard to bring clarity to the job market.
What I set out to solve:
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Who’s actually hiring for data roles?
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Which locations and companies are worth targeting?
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How do hiring trends shift month-to-month and year-to-year?
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​Amazon USA Sales Analysis Project(SQL, CTEs, Stored Procedures)
This project analyzes over 20,000 sales records from an Amazon platform to derive actionable insights into customer behavior, product performance, and sales trends.
Using PostgreSQL, I tackled SQL problems such as revenue analysis, customer segmentation, and inventory management.
The project includes data cleaning, handling null values, and solving real-world business problems through structured queries and stored procedures.
