Hi, I'm Myles

I like to make complicated things simple.Currently, I am studying Data Science and Finance at UIC.

Here are some projects I have done in the past as well as some im currently working on.

PMT Dashboard

My club's portfolio tracking that was used on a daily basis to get an overview of current holdings as well as more in depth analysis and tracking done utilizing webscraping techniques within Google Sheets to live track dividends for free.


My first take at a full blown web app which is a calendar manager. I will be adding AI compatibility to overall become your own personal calendar agent.


Tableau Dashboard for Annual Reports and Daily Activities

I designed and built a comprehensive dashboard for a team within the company. This dashboard quickly became an essential tool for tracking the progress of a specific project the company was working on. Not only did it serve as a valuable resource for day-to-day activities, but it also played a crucial role in the company's annual reports.The dashboard provided an intuitive and visually appealing interface that allowed team members to easily monitor key performance indicators (KPIs), track milestones, and analyze trends. By consolidating all relevant information into a single, easy-to-use platform, the dashboard significantly improved the team's efficiency and decision-making process.The success of this project demonstrated my ability to create practical and impactful data visualization tools, tailored to the specific needs of the company and its team members. This experience has further reinforced my passion for data analysis and its potential to drive meaningful change in a business environment.

Relational DB

Building a Robust and Scalable Relational Database

Overview:In this project, I took the initiative to design and implement my company's first relational database. The goal was to create a robust system capable of handling future growth while providing an efficient means for managing and accessing data. This involved understanding the company's data needs, defining the schema, and optimizing the database structure to ensure both performance and scalability.Key Features:Customized Schema Design: I carefully analyzed the company's data requirements and designed a customized schema that effectively captured the necessary relationships between data entities. This tailored approach ensured that the database structure was optimized for our specific use cases.Normalization: To minimize data redundancy and improve overall performance, I applied normalization techniques to the schema design. This process helped to create a more efficient database that reduced the risk of data anomalies and inconsistencies.Indexing and Query Optimization: I paid close attention to indexing strategies and query optimization techniques to enhance the database's performance. By carefully selecting the right indexes and optimizing queries, I ensured that data could be accessed quickly and efficiently, even as the database scaled.Scalability Planning: To accommodate future growth, I designed the database with scalability in mind. This involved considering potential increases in data volume and traffic, as well as planning for any necessary hardware or infrastructure upgrades.Documentation and Training: To support my colleagues in using the new relational database, I provided clear documentation and offered training sessions. This helped to ensure a smooth transition and empowered the team to effectively utilize the new system.Outcome:The successful implementation of the relational database has significantly improved the company's data management capabilities. The robust and scalable design has laid the foundation for future growth while providing the necessary tools for efficient data access and manipulation.Text

EOQ Model

Inventory Optimization using Economic Order Quantity (EOQ) Model

This project was for my final grade in a spreadsheet analysis class, it involved working with a team to help businesses optimize their inventory management using the Economic Order Quantity (EOQ) model. The EOQ model calculates the optimal order quantity for a product by considering demand, lead time, ordering costs, holding costs, and unit costs. This enables businesses to maintain the right inventory levels, meeting demand without running out of stock or incurring unnecessary holding costs.Our objectives were to help businesses:Understand the minimum inventory level required to meet demand using the EOQ calculation in our Excel project.Determine the best time to place an order for inventory or the optimal reorder point, calculated using the reorder point button in our Excel project.We developed an Excel-based tool with special features:The ability to account for multiple products (up to 10), enabling businesses to determine optimal order quantities for all products simultaneously.Two different graph options (line or bar) to visualize EOQ model results and relationships between variables, helping businesses make informed decisions about ordering and holding strategies.A random number generator for users to explore the tool without actual data, and a clear table data button for easy data resetting.Despite facing challenges such as creating a user input form connected to our Excel spreadsheet and deciding whether to include safety stock in the reorder point calculation, we successfully developed an EOQ model and reorder point calculation tool that can help businesses improve their inventory management.