Project Overview

A selection of projects demonstrating my data analytics work.

Pet Store Business

Tools Used

SQL Query, Google Sheets,Tableau

Objective

To evaluate the business performance of a pet store over a 3-year period, focusing on sales trends, customer preferences, and product category performance.

Highlights

• Data Preparation: Cleaned and pre-processed the order and store datasets to ensure accuracy and consistency.

• Exploratory Data Analysis (EDA): Identified key product categories and individual products contributing most to revenue.

• Visualization: Designed interactive dashboards in Tableau to present sales trends, top-performing items, and category breakdowns for business stakeholders.

Key Results

• Delivered actionable insights into customer buying behavior and product popularity

• Provided data-driven recommendations to support future inventory planning and restocking strategies

E-commerce Ads Campaign Evaluation

Tools Used

Microsoft Excel, Tableau

Objective

To evaluate the performance of an e-commerce advertising campaign across multiple social media platforms and provide data-driven answers to key business questions regarding conversion rates and platform effectiveness.

Highlights

• Exploratory Data Analysis (EDA): Performed comprehensive statistical analysis using measures of central tendency, dispersion, and frequency tables to uncover performance trends across campaigns and platforms.

• Experimental Design & A/B Testing:

  Applied statistical hypothesis testing to evaluate results, including calculating p-values and interpreting them against significance thresholds to determine whether to reject the null hypothesis.

• Predictive Modeling: Selected appropriate forecasting models to project future conversions, based on trends observed across multiple campaigns.

• Insight Interpretation: Synthesized findings to provide actionable recommendations for optimizing platform selection, budget allocation, and campaign targeting strategies.

Key Results

• Discovered meaningful correlations between campaign metrics such as impressions, click-through rates, and conversions

• Identified the highest-performing advertising platforms across multiple campaigns

• Developed a forecasting model to predict future conversions, supporting data-driven planning for upcoming ad campaigns

Healthcare Operations & Capacity Analysis

Tools Used

Microsoft Excel, Python,

Objective

This project analyzes hospital operational data to examine how staffing levels, patient flow, and bed capacity interact to influence overall service performance. By evaluating weekly admissions, staff availability, patient refusals, and satisfaction metrics, the analysis identifies patterns that support more efficient resource allocation and improved patient care outcomes.

Highlights

• Exploratory Data Analysis (EDA): This exploratory analysis evaluates hospital service quality and operational context by examining patient satisfaction metrics and key patient-related events. Measures of central tendency and variability are used to assess consistency in patient experiences, while frequency analysis highlights common operational events. These insights establish a data-driven foundation for understanding service performance before deeper analysis.

• Experimental Design & A/B Testing: This stage examines how staffing levels relate to patient admission outcomes within the Surgery service. By comparing staff availability and patient refusals over time, the analysis explores whether changes in workforce presence are associated with variations in service access and operational performance.

Key Results

• Staff absenteeism does not show a meaningful impact on patient refusals.

• Patient refusals occur primarily due to limited capacity rather than staffing changes.

• Most refusals happen during normal operating periods when demand exceeds available resources.

• Internal capacity constraints are the main factor influencing service access across services.