Hello!
My name is Matthew Weisman, and welcome to my data analytics porfolio!
Within this portfolio, you will find links to my completed data analysis projects, each showcasing a range of analytical skills. From data cleaning/validation and database development to EDA and data visualization, these projects encompass a wide array of data-related tasks.
To complete these projects, I used a variety of tools and software. For database work, I utilized SQL code (PostgreSQL, MySQL, SQLAlchemy) to create and analyze databases, as well as to generate reports. Additionally, I used Python to complete tasks involving data cleaning, transformation, analysis, and visualization. I also leveraged Power BI to craft interactive dashboards.
In the projects section, you'll find summaries of each project, along with links to their respective repositories for further exploration.
Thank you for visiting, and I hope you find my data analysis journey intriguing!
As a data analyst, I have a strong passion for working with data. During my college years at the University of Dayton, where I majored in Accounting with a minor in Management Information Systems, I first discovered my interest in data analysis through internships in corporate and public accounting. Much of the work I performed during these positions involved financial data analysis, which led me to realize my genuine enjoyment in hands-on using data to find and extract insights and answer business questions. This discovery sparked my curiosity to explore the field of analytics further and enhance my data analysis skills.
Through a combination of formal education, work experience, and online learning, I have gained knowledge in tools such as SQL (PostgreSQL, MySQL), Python (NumPy, Pandas, Matplotlib/Seaborn, Scikit-Learn), Power BI, Tableau, and Excel. I also hold a Data Analyst Associate certification from DataCamp, which validated my skills and knowledge. Besides my technical expertise, I have also effectively communicated my analytical findings to business stakeholders through formal presentations.
My primary aim is to leverage these analytical skills to uncover valuable insights and make a meaningful impact at a company through data analysis. For any inquires, feel free to connect with me on LinkedIn or by email at [email protected].
- SQL (PostgreSQL, MySQL)
- Python (Pandas, NumPy, MatplotLib, Seaborn, Scikit-Learn)
- Power BI
- Tableau
- Excel
- Data Cleaning/Validation
- Exploratory Data Analysis (EDA)
- Statistical Analysis
- Data Visualization
- Database Design
In this project, I developed a MySQL database to keep track of all my financial data and enable analysis, along with a Power BI dashboard to visualize spending trends. I extracted all transactions from my bank website and developed custom Python scripts to automate the bulk of the ETL process, allowing for easy maintenance of the database. SQL views were also created to act as reports, tracking KPI's such as monthly spending, spending by category, and changes in account balances. Additionally, the dashboard was linked directly to the MySQL database, providing valuable up to-date-insights in a visual manner. Note that the data in this project has been falsified to preserve privacy.
Repository Link: finances-database
Technologies/Tools: SQL (MySQL), Python (Pandas, NumPy, SQLAlchemy), Power BI, DAX
Skills: Data Modeling, Database Development, Data Wrangling, Data Cleaning, ETL, Exploratory Data Analysis (EDA), Dashboarding/Data Visualization
This project involved processing and analyzing movie data from the popular online movie database, IMDb. I extracted public IMDb datasets, cleaned and transformed this data via Python, and stored the data in a PostgreSQL database I created. I then performed analysis using a combination of SQL queries and Python code to find trends in movie production, audience reception, and actor likeness.
Repository Link: movies-analysis
Technologies/Tools: SQL (PostgreSQL), Python (Pandas, NumPy, SQLAlchemy, Matplotlib, Seaborn)
Skills: Exploratory Data Analysis (EDA), Statistical Analysis, Data Visualization, Data Cleaning/Validation, Data Transformation, Database Development, Data Wrangling
In this project, I analyzed two years of sales data from a fictional UK-based online retailer. I performed exploratory analysis to exam sales trends, such as sales by category, country, sales over time. I then wrote a Python script to streamline the generation of a marketing metrics report, calculating various different marketing metrics per quarter and evaluating the success of marketing operations.
Repository Link: retailer-eda-and-marketing-kpis
Technologies/Tools: Python (Pandas, NumPy, Matplotlib, Seaborn)
Skills: Data Cleaning/Validation, Exploratory Data Analysis (EDA), Marketing Analytics, Data Visualization, Report Generation
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent