Projects
Analysis
Analyzed the Walmart Retail Sales dataset to address two primary questions:
(1) Is the sales growth rate decreasing in most states?
(2) Which products should Walmart prioritize in each region or state to maximize profit?
Using Python for data manipulation and visualization, and SQL for querying, processed the dataset, resolved technical challenges, and derived insights. This report details the approach, including data cleaning, code structure, challenges encountered, and comprehensive responses to the assignment questions, supported by evidence from the dataset.
Click on the picture to see the report and code snippets.
Visualization
Created interactive data visualizations using Power BI that simplify complex data sets for better stakeholder understanding. These visual tools were used in an academic project on attracting investors to Saudi Arabian Tourism.
The project facilitated data-driven decision-making processes, highlighting trends in the Saudi Tourism industry using easy to understand visuals.
Click on the picture above to check out the visuals I made for this project.
Predictive
Built a predictive model using machine learning algorithms (Logistic Regression, Naive Bayes, Random Forest and Ensemble Voting Classifier) to forecast Wireless service customer churn, providing clients with insights that can help with customer retention. This project resulted in 89% accuracy in predicting customer churn using Ensemble Voting Classifier algorithm in Python.
Click on the picture above to view my stakeholder presentation and code snippets.