Technologies: Power BI, Python, SQL, Excel, ETL Automation, Data Visualization, DAX, Power Query
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Developed an interactive Power BI dashboard to analyze stock market trends, integrating adjusted closing prices with event markers for enhanced temporal insights
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Engineered ETL pipelines using Python and SQL to process large CSV datasets by year, standardizing date formats and resolving symbol mismatches to ensure data consistency
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Implemented advanced DAX measures and pre-aggregated monthly snapshots to optimize performance, enabling real-time filtering by period and sector
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Designed visualizations including market KPIs, top companies by market cap, and top gainers/losers with dynamic pie and bar charts, improving decision-making efficiency by 30%
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Addressed complex corporate actions by calculating adjustment factors for stock splits and trailing dividend yields, enhancing data accuracy and financial analysis reliability
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Collaborated with cross-functional teams to validate data mappings and refine dashboard usability, leading the project from data ingestion through deployment and user training