About Me
I’m a recent graduate in Business Analytics and Information Systems from the University of South Florida, with expertise in Python, SQL, Power BI, Tableau, and Excel. I’ve worked on projects like designing hospital databases, analyzing global sales trends, and creating automated Excel dashboards. I specialize in transforming complex data into clear, actionable insights and am passionate about applying my skills to solve real-world challenges in technology, healthcare, and e-commerce. I’m eager to learn, grow, and contribute to innovative, data-driven solutions.
Skills
Excel | Power BI | Python | Tableau | SQL
Data Visualization
Business Intelligent
Time Management
Problem Solving
Featured Projects
SQL and Power BI
Customer Churn Analysis Dashboard
An end-to-end customer churn analysis solution using SQL and Power BI, featuring data preprocessing, interactive dashboards, and actionable insights to improve customer retention.
Python
Nashville Housing Data Analysis: Trends and Insights into Property Sales
This project analyzes Nashville housing data to uncover key trends in property sales, including price fluctuations, high-performing neighborhoods, and the impact of features like bedrooms and building value on sale prices. Using Python for data analysis and visualization, the insights support real estate decision-making with clear and compelling visuals.
Tableau
KAT Manufacturing Sales Performance Dashboard
Sales Performance Analysis Dashboard
Interactive Tableau dashboard for KAT Manufacturing, providing insights into revenue distribution, sales trends, and top-performing segments to support strategic decision-making.
Excel
Personal Budget Excel Dashboard Project
An automated Excel dashboard was developed to track income and expenses, providing real-time totals and categorized spending insights for effective financial management.
Professional Certifications
My growing list of proprietary, skills-based certifications
Microsoft Power BI Data Analyst | expected 2025
Google Data Analytics | Issued 2023
SQL and Power BI| Customer Churn Analysis Dashboard
🌟 Project Overview:
This project focused on building an end-to-end churn analysis solution using Power BI and SQL, designed to identify and analyze customer churn patterns. The interactive dashboard provided actionable insights into churn rates, customer behavior, and business trends, empowering stakeholders with data-driven decision-making tools to improve customer retention strategies.🤔 Key Questions Addressed:
1️⃣ How can SQL be leveraged to query and preprocess large datasets for churn analysis?
2️⃣ What are the primary factors driving customer churn, and how can they be measured effectively?
3️⃣ How do churn trends affect overall business performance?**
4️⃣ What visualization techniques best convey churn insights to stakeholders?🛠️ Steps Taken for the Analysis:
1️⃣ Data Extraction and Cleaning:
- Utilized SQL queries to preprocess and clean raw customer data, ensuring accuracy and consistency.2️⃣ Data Transformation:
- Structured data for analysis, focusing on essential metrics like churn rates, customer segmentation, and behavioral patterns.3️⃣ Dashboard Design:
- Built an interactive Power BI dashboard featuring KPIs, trend analyses, and heatmaps to deliver a holistic view of churn insights.4️⃣ Automation:
- Scheduled SQL queries and Power BI data refreshes for real-time insights, enabling up-to-date analysis at any moment.5️⃣ Final Review:
- Ensured the dashboard’s usability, clarity, and alignment with business objectives through rigorous testing and refinement.✨ Key Takeaways:
- SQL Mastery: Robust preprocessing and transformation in SQL provide the foundation for scalable, large-scale churn analysis.
- Actionable Insights: Identifying churn factors offers clear strategies for improving customer retention.
- Visual Storytelling: Power BI transforms complex data into engaging visuals that communicate trends effectively.
- Comprehensive Solutions: Building an end-to-end churn analysis platform demands a mix of data modeling, analytical skills, and user-focused design.
Python | Nashville Housing Data Analysis: Trends and Insights into Property Sales
🌟 Project Overview
This project analyzes Nashville housing data from 2013 to 2016, focusing on uncovering trends in property sales, market performance, and housing characteristics. By leveraging Python for data cleaning, analysis, and visualization, key insights were derived to assist real estate decision-making and market evaluation.🤔 Key Questions Addressed
1️⃣ What are the trends in property sales prices over time, and how do they vary by property type?
2️⃣ Which neighborhoods and property types contribute the most to market value?
3️⃣ How do property features (e.g., bedrooms, bathrooms, building values) influence sale prices?
4️⃣ What are the most common housing types, and how do their average sale prices compare?🛠️ Steps Taken for the Analysis
1️⃣ Data Extraction and Cleaning
- The dataset was imported from a CSV file.
- Irrelevant columns (e.g., identifiers, owner names) were removed.
- Missing and incomplete records were filtered to ensure data integrity.2️⃣ Data Transformation
- Metrics like total value, building value, and acreage were calculated for analysis.
- Data was categorized by property type, sale year, and neighborhood for better segmentation.3️⃣ Dashboard/Model Design
- Python libraries (e.g., Matplotlib, Seaborn) were used to create visualizations, including:
- Line charts to track sale price trends over time.
- Heatmaps to highlight neighborhood performance.
- Scatter plots to analyze relationships between features (e.g., bedrooms, sale price).4️⃣ Final Review
- The dataset and insights were validated against project objectives.
- Anomalies and outliers were further analyzed for additional insights.✨ Key Takeaways- Technical Expertise Demonstrated:
Using Python skills, including Pandas for data manipulation and Matplotlib/Seaborn for effective data visualization.- Actionable Insights Discovered:
Identified high-performing neighborhoods and property types, and revealed key factors influencing property sale prices (e.g., finished area, land use).- Effective Communication and Visualization:
Delivered clear, visually engaging insights through professional visualizations, aiding in better decision-making and understanding.- Holistic Problem-Solving Approach:
Combined technical expertise, analytical thinking, and strategic communication to address real-world housing market challenges effectively.
Tableau | KAT Manufacturing Sales Performance Dashboard
✨ Project Overview:
This project involves creating a Tableau dashboard to analyze sales performance and revenue trends for KAT Manufacturing. By leveraging Tableau’s visualization capabilities, the dashboard provides actionable insights into key business metrics. The primary objective is to empower decision-makers with a clear understanding of revenue distribution, top-performing segments, and sales trends to drive strategic growth and operational efficiency.🤔 Key Questions Addressed:
1. How is revenue distributed across different product categories and divisions?
2. What are the trends in revenue and sales performance over time?
3. Who are the top customers driving significant sales?
4. How do sales trends vary geographically?🛠️ Steps Taken for the Analysis:1. Data Extraction and Cleaning:
- Data was sourced from KAT Manufacturing’s sales database.
- Necessary transformations were performed, including:
- Removing duplicates
- Standardizing formats
- Handling missing values2. Data Transformation:
- Key metrics calculated include:
- Total revenue
- Quarterly sales
- Top customer contributions
- Data was structured to align with Tableau’s visualization requirements for seamless integration.3. Dashboard/Model Design:
- Interactive dashboards were created using Tableau, including:
- Revenue by Category: Visualizes revenue contributions by product categories.
- Sales by Division Map: Highlights geographical sales trends.
- Top Customers: Identifies high-value customers.
- Quarterly Sales Trends: Provides time-series analysis of sales performance.4. Final Review:
- Conducted rigorous testing to ensure accurate data representation and user-friendly navigation.
- Incorporated stakeholder feedback for further refinement.✨ Key Takeaways:- Skill/Tool Mastery:
- Demonstrated expertise in Tableau for data visualization and storytelling.- Insights/Strategies:
- Identified critical revenue drivers and sales patterns, enabling targeted strategies for growth.- Communication/Design:
- Delivered clear and visually appealing dashboards, simplifying complex data interpretation.- Comprehensive Approach:
- Combined technical proficiency, analytical rigor, and business acumen to deliver impactful insights.This project underscores the value of using Tableau for translating raw data into meaningful business insights while ensuring clarity and effectiveness.
Excel | Personal Budget
This project involved creating an automated Excel dashboard to track personal income and expenses. The dashboard calculated totals, categorized spending, and used visual charts to showcase trends in income, expenses, and savings. It provided a user-friendly tool for efficient financial management and improved insights into financial patterns.Questions of Interest:
1-How can income and expenses be tracked in real-time for accurate financial monitoring?
2-What are the primary categories of spending, and how can they be analyzed effectively?
3-How do income and expense trends impact overall savings?
4-What visualization techniques make financial data easier to interpret?Steps Taken for the Analysis:
1-Designed the Excel sheet layout, including sections for income, expenses, and savings.
2-Created automated formulas to calculate totals and categorize spending by type.
3-Organized data into structured tables for easy manipulation and analysis.
4-Used Excel’s charting features to create visual trends for income, expenses, and savings.
5-Reviewed the dashboard for accuracy, usability, and clarity.Key Takeaways:
1-Automation in Excel can significantly improve the efficiency of financial tracking.
2-Categorizing expenses provides valuable insights into spending habits and areas for savings.
3-Data visualization simplifies understanding and decision-making in financial management.
4-Building dashboards requires a balance of technical skills and user-focused design.