Delivered an end-to-end cryptocurrency analytics solution using real-time data from Binance and CoinGecko APIs, processing over 5,800 time-series records across multiple cryptocurrencies. Analyzed historical data spanning April 2025 to April 2026, covering major cryptocurrencies such as Bitcoin (BTC), Ethereum (ETH), Binance Coin (BNB), XRP, and Cardano (ADA), including price (Open, High, Low, Close), trading volume, and market capitalization. Engineered a data pipeline by integrating OHLCV data from Binance with market data from CoinGecko, enabling comprehensive multi-source financial analysis. Performed data cleaning and transformation to structure time-series datasets, ensuring data quality and accuracy for downstream analysis. Conducted exploratory data analysis (EDA) using Python (Pandas, Matplotlib, Seaborn) to uncover trends, volatility patterns, and inter-asset relationships. Applied advanced financial metrics, including Sharpe Ratio and Maximum Drawdown, to evaluate risk-adjusted performance and market behavior. Developed an interactive Power BI dashboard featuring KPI cards, filters, and multi-page navigation to deliver dynamic insights into price trends, volatility, and comparative performance. Key Insights: • Bitcoin and Ethereum dominate overall market trends • High-volatility assets exhibit greater risk and deeper drawdowns • Strong inter-asset correlation limits diversification benefits • Large-cap cryptocurrencies provide superior risk-adjusted returns Impact: Enabled data-driven investment analysis by providing clear visibility into cryptocurrency performance, risk exposure, and market dynamics. Tools & Technologies: Python, Pandas, NumPy, Matplotlib, Seaborn, Power BI, REST APIs (Binance, CoinGecko) Skills: Data Analysis | Financial Analysis | API Integration | Data Visualization | Business Intelligence