Portfolio, Project, & Product Management
SQL
Microsoft Excel
Tableau
Microsoft Power Automate
Python
Microsoft Power BI
R
Salesforce
Food Delivery Analysis (Excel)
Excel | Exploratory Data Analysis
Utilizes real world marketing campaign data
Utilized only Excel for data analysis and visualization
Provided a through write up to guide further marketing team decisions
MASS Schools Data Visualization (Tableau)
Tableau | Data Visualization
Created data visualization utilizing over 1800 different Massachusetts schools' performances across 100s of features
Utilized KPIs, Bar Charts, Scatter Plots, and Area Charts to easily communicate data to stakeholders
Presented dashboard to stakeholders via recorded video
Financial Analysis of World Bank Loans in Honduras (SQL)
SQL | Exploratory Data Analysis
Data-mined 1.3 million rows of real banking transactions, as of Dec 2024, to find trends, comparisons, and outliers
Provided a concise write up containing general funding, loan repayment, sector and project analysis, and comparative analysis to stakeholders.
About
Hi, I'm Joe & welcome to my portfolio! Over the past few years, I've become a real nerd over data. Once I realized that I could take a bunch of obscure facts and numbers and help people see the story they were telling, I was hooked.As a solutions architect, I see problems as puzzles to solve and data as the missing puzzle pieces. In previous experiences as a Portfolio and Project Manager, I learned how to communicate well and support teams and organizations in their goals!I'm proficient in analyzing data with:
- Excel
- Tableau
- SQL
- Python
- RAnd I'm looking to help a company extract insights and tell better stories with their data. If you'd like to contact me, feel free to email me: [email protected]
Analyzing Food Delivery Services Like DoorDash: Discovering Food Trends Through Data
Growing up, I always had a love-hate relationship with driving. I love the freedom, but hate the process. While I enjoy a good meal, the process of driving, waiting in line, and enduring crowds has often pushed me towards food delivery options. This personal preference inspired me to dive into a project analyzing food delivery trends, specifically through the lens of iFood, a Brazilian counterpart to DoorDash. I wanted to uncover what motivates people, like me, to opt for delivery instead of dining out or driving to pick food up myself.
Why This Project?
I’m curious about the changing landscape of food delivery. Changes in trends are often sparked by an underlying story. For me, it's my dislike for driving and my passion for discovering new foods, but is it the same for everyone? What are the factors that drive people to use food delivery services? This project not only aligned with my personal interests but also tackled a relevant business problem. Understanding consumer trends in food delivery can offer valuable insights for businesses looking to thrive in the competitive food market.
What Readers Will Gain
By the end of this article, you’ll gain insights into:
The seasons that see a peak in food delivery usage
How income influences food delivery habits
Spending patterns among food delivery users
Key Takeaways
Food delivery sees spikes in user sign-ups during winter and summer.
Higher income levels are linked to increased food delivery spending.
While more people are having food delivered, budgets are still relatively small.
Dataset Details
I used a dataset sourced from https://github.com/nailson/ifood-data-business-analyst-test/blob/master/ifood_df.csv, which included over 2000 rows of information from 2018. This dataset contained valuable income and family data, although it was modified for educational purposes. It provided a solid foundation for analyzing food delivery trends, as it captured a diverse range of users.
Analysis Process
The analysis involved several steps:
Data Cleaning: Ensured the accuracy of the dataset by removing any inconsistencies.
Data Transformation: Organized the data to hone in on key variables like income, spending, and user sign-up dates.
Visualization: Created scatter plots and bar charts to illustrate spending habits and user trends.
Before starting analysis, I cleaned the dataset by removing over 150 duplicate entries, resulting in 2,021 unique records across 30+ columns. Utilizing Microsoft Excel, I used functions including SUM, COUNT, MAX, MIN, and AVERAGE, as well as pivot tables and VLOOKUP and XLOOKUP to capture insights from the data.
Visuals & Insights
Months Joined Bar Chart: This chart reveals the months when users are most likely to join food delivery platforms. Notably, winter and summer months are peak times, likely influenced by weather and holiday activities.
Months Joined Steady with peaks in Winter and Summer
Income vs. Total Spend Scatter Plot: This visual shows how user income correlates with their spending on food delivery. As income increases, so does the likelihood of spending more on delivery services.
Income vs Total Spent showing a clear trend up as income increases
Total Amount Spent Histogram: This histogram indicates that most customers spend less than $315 annually on food delivery. This finding suggests that while many people use delivery services, they may do so in moderation.
Majority of food delivery customers are spending less than $315 food delivery in a year
Main Takeaways
From my analysis, a few key insights emerged:
The seasonal spikes in food delivery sign-ups suggest that external factors, such as weather and social events, significantly influence consumer behavior.
The consistent growth in food delivery increase per income indicates a shift in how people view convenience in dining, especially as lifestyles become busier.
Understanding these trends can help food delivery services tailor their offerings and marketing strategies to meet consumer needs better.
Conclusion and Personal Reflections
This project taught me a lot about the intricate relationships between income, seasonality, and consumer behavior in food delivery. One of the biggest challenges I faced was making sense of the data trends and their implications. However, overcoming this challenge deepened my understanding and sparked my interest in data analysis.Moving forward, I hope to continue exploring similar projects. Each time we stop and really think about the world around us, we can find data begging to tell a story.
Call to Action
I would love to hear your thoughts or answer any questions you might have about food delivery trends or data analysis. Let’s chat!
Financial Analysis of World Bank Loans in Honduras
Reflecting on my college days, I often think of a dear friend from Honduras who opened my eyes to the unique contrasts of her home country. Amidst the vibrant culture, rich food, and stunning landscapes, there lies a stark reality of violent crime and severe poverty. This personal connection sparked my curiosity about how Honduras is faring economically, especially in relation to its neighbors and bigger players on the global stage.
Why This Project?
This project became a meaningful pursuit for me, fueled by my desire to understand how international funding influences a nation like Honduras. I wanted to uncover the intricate details of the World Bank loans extended to the country and how they impact various sectors. It was not just about numbers; it was about finding the story behind them and exploring the paradoxes my friend described.
What Readers Will Gain
In this article, readers will gain insights into the financial landscape of Honduras, specifically regarding World Bank loans. I’ll share the surprising findings from my analysis and explore what they mean for the country’s economy. You’ll walk away with a better understanding of the complexities behind international loans and the human elements involved.
Key Takeaways
Honduras receives a significant amount of funding in comparison to El Salvador, which only gets 1.08% of the total amount of Honduras.
A large portion of loans are dedicated to disaster relief efforts.
The most significant ongoing project aims at reducing citizen violence.
Natural disasters and climate change pose major risks to Honduras' future economic efforts.
Dataset Details
For this analysis, I used a dataset from the World Bank Group, which included over 1.3 million transactions as of December 31, 2024 Linked here. This dataset was rich with information and allowed me to explore various angles of funding and repayment trends. It was essential for my analysis, as real-world data lends credibility and depth to the findings.
Analysis Process
This journey started with data mining to clean and organize the 1.3 million rows of banking transactions. I transformed the raw data to make it manageable and visualized key trends. One surprise was seeing the significant impact of natural disasters reflected in the 2020 data. I had anticipated some correlation, but the extent of it caught me off guard. It made me realize how interconnected economic factors are with real-world events.
Visuals & Insights
Total Funding to Honduras: This visual illustrates the total amount of funding provided by the International Development Association (IDA) to Honduras in US dollars. It shows the scale of investment in the country, signaling international interest and support.
SQL Statement utilizing SUM and WHERE to gather total funding information
Information retrieved from above SQL Statement
Top 5 Projects: Here, we can see which projects received the most funding. Notably, disaster relief projects take up a considerable portion, highlighting Honduras's vulnerability to natural calamities.
SQL Statement utilizing WHERE and AND, as well as ORDER BY, DESC, and LIMIT to gather and order data
Information retrieved from above SQL Statement
Change in Funding Over the Years: This graph tracks the trend of IDA funding over time, giving insights into how the financial support has evolved and its possible correlation with economic conditions. It was particularly insightful to see how hurricanes in 2000 increased funding sharply.
SQL Statement utilizing STRFTIME(), SUM, WHERE and GROUP BY, as well as ORDER BY and ASC, to gather and order data
Information retrieved from above SQL Statement annotated to 2002
Funding Repayment Status: Here, we see how much of the extended IDA funding has been repaid - around 51%. This metric is crucial for assessing long-term sustainability.
SQL Statement utilizing SUM and WHERE to gather and order data
Information retrieved from above SQL Statement
Ongoing IDA-Funded Projects: This visual highlights the largest ongoing project, which focuses on citizen violence reduction, reflecting a need for social stability.
SQL Statement utilizing SUM, WHERE and GROUP BY, as well as ORDER BY and DESC, to gather and order data
Information retrieved from above SQL Statement
Comparative Funding Analysis: Finally, comparing Honduras' funding to that of neighboring countries like Guatemala and El Salvador reveals significant disparities and raises questions about regional economic strategies.(Insert Visual Q12)
SQL Statement utilizing WHERE, GROUP BY, as well as ORDER BY and DEC, to gather and order data to compare trends among countries
Information retrieved from above SQL Statement
Main Takeaways
From my analysis, a few key insights emerged:
I learned that economies are intricate systems where everything is interconnected. The funding from the World Bank isn’t just about money; it involves human factors, government policies, and real-life challenges like natural disasters.
Social stability, both in terms of equality and crime, as well as relief from natural disasters have placed Honduras in a spiral that must be addressed if stability is to be attained in the region.
The stark contrast in funding between Honduras and its neighbors highlights not only economic disparities but also the pressing need for targeted support in vulnerable areas - specifically in disaster resistant infrastructure and reduction of violent crime.
Conclusion and Personal Reflections
Reflecting on this project, I am amazed at how much I learned about the economic landscape of Honduras. The challenges were real—wading through millions of rows of data was no small feat! But each obstacle pushed me to think creatively and find ways to extract meaningful insights.This experience has reshaped my perspective on economic development and solidified my goal to engage in meaningful projects that consider the human side of financial assistance.
Call to Action
I would love to hear your thoughts or answer any questions you might have about SQL or data analysis. Let’s chat!