Jayashree Sambasivam Muralidharan

Data analytics professional with a focus on utilizing Power BI, Tableau, Python, and SQL for impactful data analysis and visualization. Demonstrated success in driving data-driven decisions and optimizing processes. Excellent communication and presentation skills, with a track record of achievements in challenging settings. Experienced in applying innovative learning strategies to improve academic outcomes.

• Essentials of Data Analytics, UT Austin
• Microsoft PL-300

FOOD HUB PROJECT USING PYTHON Project: Restaurant Demand and Delivery Optimization Analyzed historical customer order data to uncover key insights into restaurant demand, customer behavior, and delivery efficiency. Identified high-demand restaurants, peak order times, and delivery patterns, leading to optimized restaurant partnerships and marketing strategies. Conducted statistical and time-series analysis to improve delivery times and customer satisfaction, resulting in a 12% reduction in average delivery time. Built predictive models to forecast demand, optimizing delivery personnel allocation and improving on-time deliveries by 15%. Utilized Python (Pandas, NumPy), SQL, and machine learning techniques to derive actionable insights that enhanced customer experience and operational efficiency., NEW WHEELS – SQL PROJECT Project: Quarterly Business Health Report Analyzed sales, customer feedback, and after-sales data to identify trends affecting business performance. Used SQL to extract, clean, and analyze key metrics such as sales trends, return rates, and service feedback. Delivered a data-driven quarterly report for the CEO with actionable insights and recommendations to address sales decline and improve customer satisfaction. Provided strategic recommendations for enhancing customer retention and service quality, contributing to informed business decisions., MOVIE LENS – POWER BI PROJECT Project: Analysis of Classic Movies and User Preferences Analyzed classic movie data (pre-2000) to provide insights for the "Movie Talkies: Classic" edition. Explored movie releases, genre diversity, user demographics, and preferences across genders, age groups, and occupations. Created an interactive dashboard using Power BI visualizing top-rated classic movies, user engagement, and rating trends over time. Identified key patterns in genre preferences, rating behaviors, and demographic engagement to guide Movie Lens promotional strategy. Delivered actionable insights to enhance audience targeting and engagement with classic film., GLOBAL VIDEO GAME SALES – TABLEAU PROJECT Analyzed global video game sales data, creating an interactive Tableau dashboard to visualize trends across platforms, genres, and regions. Developed key visualizations, including Yearly Global Sales Trend and Genre-wise Global Sales. Integrated filters for interactivity, allowing users to explore sales data by platform, genre, publisher, and year. Identified peak sales periods and trends in the video game industry. Highlighted popular genres and regional sales differences, guiding marketing and development strategies.