Full-Stack Data & Automation Professional
Data Analytics, Automation & Enterprise Solutions Architect
Delivering actionable insights and business value through data, code, and intelligent systems
Welcome to my portfolio! I'm a results-driven data professional with 8+ years of experience I’ve had the opportunity to design and deliver high-impact analytics and automation solutions across industries. My career has been fueled by a passion for turning complex data into clear insights—and for building systems that scale.
I’ve led the development of enterprise-level applications, built predictive models using machine learning, and created real-time dashboards that drive better decisions across operations, finance, and marketing. Whether it’s through Microsoft 365, Power BI, Python, SQL, or full-stack development, my work centers around one mission: enabling organizations to operate smarter through data.
This site showcases some of the projects, tools, and strategies I’ve developed to empower businesses and teams. From streamlining inventory operations to building automated reporting pipelines, each project reflects my drive to improve efficiency, clarity, and performance through data systems.
If you're looking to collaborate, explore a custom data solution, or discuss opportunities in BI, automation, or digital transformation—let’s connect.
My Projects
Power BI Visualization
VISUALIZATION IN POWER BI
This project focused on transforming raw enrollment data into a compelling, interactive dashboard using Power BI, with the goal of communicating insights to both technical and non-technical stakeholders.
I developed a dynamic state-level visualization that maps the geographic distribution of students enrolled in the BS Data Analytics program. The dashboard leverages Power Query, DAX, and custom visuals to enable easy filtering and exploration by state and enrollment metrics.
By combining analytical storytelling with a clean, executive-friendly layout, the project demonstrates how data visualization can bridge insights and decision-making—making complex patterns immediately accessible to faculty, administrators, and leadership teams.
Artificial Intelligence
Personalized Recommendation Engine Using Machine Learning
This project involved the design and development of a machine learning–driven recommendation system that predicts user interests and delivers personalized activity suggestions.
Using an adaptive quiz interface, the system dynamically evolves based on user input—refining its recommendations through behavioral learning patterns and personality indicators. Built using Python and key ML libraries, the model leverages supervised learning techniques to generate tailored user experiences.
The project demonstrates how AI and intelligent systems can enhance engagement, personalization, and decision support across digital platforms.
Business Systems Analysis
Strategic Recommendations for Process Optimization
This project involved conducting a comprehensive evaluation of multiple information management systems to identify opportunities for improving organizational efficiency. I analyzed system performance, workflows, and data governance practices to develop a set of strategic recommendations tailored to a simulated business scenario.
The proposed solutions focused on streamlining operations, enhancing data quality, and integrating lean methodologies to reduce waste and increase process transparency. This work demonstrates my ability to translate technical analysis into actionable business insights that support high-impact outcomes in fast-paced, dynamic environments.
Data Quality Plan for M&A Integration
Establishing Data Standards During Acquisition
In this project, I developed a Data Quality and Integration Plan in preparation for a mock corporate acquisition between Bruce, Inc. and Wayne Enterprise. The objective was to ensure a seamless data merger by defining protocols for data standardization, validation, and system readiness.
I created a formal data request framework to extract critical information from the acquired company, enabling effective analysis, system alignment, and governance planning. The project emphasized maintaining data integrity and compliance throughout the cleaning, merging, and transformation processes.
This work highlights my ability to create scalable data plans for complex integration scenarios, ensuring clean, trustworthy data for future use.
Predictive Crime & Storm Impact Analysis
R-Based Data Report for Public Safety Planning
In this project, I created a comprehensive data report for the Miami Police Department using R programming to analyze historical storm and crime data. The goal was to provide the department with actionable insights that could support proactive crime prevention and resource planning.
Using statistical modeling and data visualization techniques in R, the report identified correlations between storm patterns and crime trends—empowering the department to anticipate high-risk periods and optimize response strategies.
This project showcases the application of data science in public safety, combining real-world impact with technical analysis and reporting.
Project Management Workflow Redesign
Optimizing Processes for Software Development
This project involved designing a streamlined project plan to improve workflow efficiency and implement custom solutions for a new software release.
Key responsibilities included identifying bottlenecks, enhancing task coordination, and proposing additional features and recommendations to support the successful rollout. The project emphasized agile practices, stakeholder alignment, and cross-functional collaboration to drive timely and effective project delivery.
Predictive Modeling with Linear & Multiple Regression
​Forecasting Outcomes Using R and Python
In this project, I developed and tested multiple regression models using both R and Python (pandas, statsmodels) to predict outcomes based on structured sample datasets. The analysis included both simple linear regression and multivariate regression techniques to evaluate variable relationships and optimize model performance.
The models were trained on provided datasets and validated for accuracy using statistical metrics. This project highlights my ability to apply predictive analytics techniques to extract meaningful insights and support data-driven forecasting.
Advanced Regression Analysis for Real Estate Forecasting
Multiple Regression with Qualitative Variables & Interactions
In this project, I used historical housing market data to build predictive models estimating home sale prices. The analysis incorporated multiple regression techniques, including interaction terms, quadratic regression, and qualitative variables (e.g., location, condition, property type).
By exploring relationships between key housing attributes and sale outcomes, I developed models that revealed significant variable interactions and non-linear effects, improving the accuracy of price predictions. This project demonstrates my ability to apply advanced regression methods and translate complex variable behavior into actionable forecasting tools.
Economic Simulations & Microeconomic Principles
Memorandum Report on Business Decision-Making
This report explores key microeconomic concepts through a series of interactive simulation games designed to reflect real-world business decision-making. Each simulation highlights principles such as supply and demand, opportunity cost, resource allocation, and marginal analysis.
The project summarizes my findings and reflections, connecting theoretical economic frameworks to practical outcomes. By analyzing the results and applying them to real-life scenarios, I demonstrated how foundational economics can support strategic thinking and data-informed business planning.
Exploratory Data Analysis (EDA)
Uncovering Patterns, Trends, and Hypotheses
This project focused on performing exploratory data analysis (EDA) to identify hidden patterns, correlations, and trends within raw datasets. Using tools like Python (pandas, matplotlib, seaborn) and Power BI, I applied data visualization, summary statistics, and data mining techniques to uncover meaningful insights.
The goal was to generate initial hypotheses for further analysis while improving data quality and structure. This project highlights my ability to transform unstructured data into valuable stories that guide strategic decisions and deeper modeling.
Project Analysis & Strategic Recommendations
Optimizing Project Performance Through Data-Driven Insights
This project focused on analyzing key project data to identify performance gaps and develop targeted, data-backed recommendations. The analysis evaluated areas such as timeline efficiency, resource utilization, risk exposure, and stakeholder alignment.
Based on these insights, I proposed actionable improvements to project timelines, budgeting, team collaboration, and risk management processes—resulting in a more structured approach to achieving successful project outcomes. This work demonstrates my ability to translate analytical findings into strategic project enhancements.
Leadership & Management Principles
Guiding Vision and Driving Results
This project explored the complementary roles of leadership and management in achieving organizational success. While leadership is centered around setting a vision, inspiring teams, and driving innovation, management focuses on planning, organizing, and allocating resources to execute that vision efficiently.
Through research and analysis, I examined how effective organizations balance both skill sets—strategic thinking and operational control—to build high-performing teams and deliver consistent results. This work reinforced my understanding of how strong leadership and disciplined management are both essential to driving sustainable performance in dynamic environments.
Data Privacy & Compliance
Protecting Information in a Digital Age
As data collection and digital technologies evolve, data privacy has become a critical concern for individuals and organizations alike. This project focused on understanding and applying privacy best practices, including the handling of sensitive information, regulatory compliance (such as GDPR and CCPA), and secure data governance.
The work emphasized the importance of maintaining confidentiality, integrity, and transparency when managing user data—reinforcing the ethical responsibility that accompanies analytics, automation, and AI development.
SKILLS
VISULIZATION
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Excel
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Tableau
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Google Data Studio
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Power BI
SAS
MatLab
R
Machine Learning
PROGRAMMING
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SQL
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Python
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VBA
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Macro
Core Proficiencies
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Microsoft Excel, Word, PowerPoint, Outlook
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Python
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Writing Procedures & Documentation
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SQL
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QuickBooks
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Smart Draw
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Google Analytics
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Tally
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PMS (Project Management Systems)
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Salesforce
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Jupyter
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Power BI
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Data Pipelines
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Machine Learning
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API Integration
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Power Automate
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Excel Macros (VBA)
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Advanced Excel
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Azure
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Data Governance
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Data Quality Assurance
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SAS
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SPSS
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Data Integration
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Time-Series Analysis
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Predictive Analytics