Data Harmony: Bridging Analytics and Passions in My Portfolio

Check out my projects, bio and resume below!

Uncovering Box Office Success: Analyzing Movie Data and Gross Revenue Correlations with Python

Lights, camera, analysis! In this project, I embarked on a blockbuster journey to uncover the secrets of the movie industry using a dataset imported from Kaggle into Jupyter Notebook. My primary goal was to reveal the correlation between various factors, such as ratings and budgets, and their impact on gross revenue. The project unfolded in several key stages:
- Initial Import of Data: I began by importing a comprehensive movie dataset from Kaggle into Jupyter Notebook.
- Hypothesis Formation: I posited that higher ratings and larger budgets would correlate with higher gross revenue.
- Utilization of Pandas: Leveraging Python's powerful data manipulation library, Pandas, I cleaned the data and defined the necessary data types to ensure accuracy in the analysis.
- Data Cleaning: This crucial step involved removing any inconsistencies and ensuring the dataset was pristine for analysis.
- Creating Visualizations: Using various visualization tools, I illustrated the relationships between different factors and their impact on box office performance.
- Finding the Ultimate Categories: The final analysis aimed to identify the categories that had the highest correlation with box office success.
By the end of this project, I was able to provide a data-driven narrative on what factors truly make a movie a box office hit.

Race to Insights: An F1 Analysis | Part 1 - The Data, SQL and ETL

Formula 1 (F1) is the pinnacle of motorsport, combining high-speed thrills and advanced technology. Beyond the excitement of the races, F1 is deeply driven by data. Each race weekend, teams gather vast amounts of information from numerous sources, including the cars' hundreds of sensors, weather forecasts, tire wear, and driver performance. These sensors generate millions of data points per second, providing real-time insights into engine temperatures, braking patterns, fuel consumption, and more.

Our project focuses on compiling and analyzing race data for every lap ever driven in the sport. By exploring this extensive dataset, we aim to uncover patterns and insights that have shaped the outcomes of races throughout F1 history. This analysis will provide a deeper understanding of the sport's intricacies and the critical role of data in driving success.

Stepping into Cultural Resonance: Unraveling Virgil Abloh's Influence using Excel and Tableau

"Introduction"
In the vast landscape of sneaker culture, we delve into a compelling narrative centered around the profound impact of Virgil Abloh's "The Ten" collection. Our exploration navigates through the intricacies of data, offering an in-depth analysis of StockX sales that transcends numerical values.
As we immerse ourselves in this journey, the data becomes more than just statistics; it transforms into a storytelling tool that unveils the cultural resonance and market dynamics shaped by the release and subsequent events surrounding "The Ten." Join me in unraveling the threads that connect artistry, market trends, and the intricate dance of anticipation and release within the sneaker world.

Navigating Flight Delays: A SQL and Tableau Analysis of DFW Departures

Embark on a data-driven journey exploring flight delays departing from Dallas/Fort Worth International Airport (DFW)!

In 2022, DFW secured its position as the second busiest airport in the United States, trailing behind Atlanta Hartsfield-Jackson. With a remarkable 73.3 million passengers passing through its terminals, DFW plays a pivotal role in shaping the dynamics of air travel nationwide. Through the lens of SQL analysis, this project aims to unravel the intricacies of domestic flight delays from DFW, shedding light on patterns, insights, and potential improvements within this bustling aviation hub.

About me

I'm Zachary Simons, a dynamic individual who finds equal fascination in exploring the intricate patterns within data and the strategic intelligence of business analytics.

Dynamic Analyst: With six years of experience in the dynamic realm of analytics and education, I'm passionate about deciphering the intricate patterns within data and translating them into actionable insights.

Analytical Expertise: My journey began with a foundation in Business Intelligence, where I honed my skills in SQL, Python, Data Visualization, and Microsoft Office. These tools have been instrumental in my ability to navigate complex datasets and extract meaningful insights.

Professional Milestones: Throughout my career, I've achieved significant milestones, leveraging my expertise to drive impactful strategies and solutions. Whether it's optimizing business processes, identifying trends, or forecasting outcomes, I thrive on the challenges presented by data analytics.

Seamless Integration: What truly sets me apart is my ability to seamlessly integrate analytics into various domains. From enhancing decision-making processes to driving business growth, I've demonstrated a knack for bridging data-driven insights with real-world applications.

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