nihit كومار

Analyzed Spotify dataset to unveil song popularity drivers using Python, University of Strathclyde Link Jan '23 — Feb '23 • Conducted meticulous data exploration to rectify null values and duplicates. • Employed data visualization techniques to gain insights into the dataset. • Implemented regression analysis with Linear Regression, Decision Tree, and Random Forest models. • Achieved lowest RMSE of 8.19 with Random Forest Regression; explored advanced techniques for enhanced predictions. Bank Loan Analysis: SQL Insights & Tableau Visualization, Personal Link Nov '23 — Jan '24 • Applied SQL and Tableau skills (Data modelling, Data transformation, Report design). The goal was to monitor key loan metrics and understand the factors influencing banks to give loans. • Gathered, transformed, modelled data, and analyzed loan application data, demographics, and key performance metrics (KPIs), ultimately delivering a cohesive report with actionable insights on maximizing Good Loan Applications. • Created a robust report, offering actionable insights through visualizations, trends, and demographics, empowering data- driven improvements to DTI. Data-Driven Sales Strategy Enhancement: Tableau Dashboard Insights, Personal Link Apr '23 — May '23 • Utilized Power Automate to gather sales data, established an SQL database, and seamlessly imported it into Tableau. • Conducted Exploratory Data Analysis (EDA) and crafted informative Views. • Created Tableau Dashboards with sales KPIs. • Implemented parameterized queries for adaptable insights. Analyzed Perth Housing Dataset for price forecasting using Python, University of Strathclyde Link Jun '23 — Jul '23 • Cleaned, described, and correlated data for insights. • Applied Linear Regression and Random Forests for price prediction. • Utilized K Means Clustering for house cluster identification. • Evaluated model limits, refining future strategies. • Contributed to evidence-based housing policy development.