We all have trouble managing our money as students. Most of the time we don't even realize we go over our budget during the month. This app solves the problem by allowing the user to set goals, and connect their banking information to monitor their spending.

What it does

The application has two levels, first is the user-specific spending insights, and the second is an enterprise tool that allows for marketing insights.

There are tools such as geotagged spending habits, and population clustering.

How we built it

We used TD-DaVinci for all the data that is being used to simulate the application. We used JavaScript/HTML/CSS to build the web app, and we hosted the backend on Microsoft Azure and Google Cloud Platform. We used python and sckit-learn to build an unsupervised learning solution.

Challenges we ran into

We had challenges with processing big data without the big data tools, it caused some computers to be non-functional for many hours due to lack of memory. We additionally had many challenges with Google Maps. We were initially using Angular 8 for the frontend, but the angular Google maps package was still under development and had many bugs. This caused our team to switch all our angular typescript components to traditional HTML/CSS.

Accomplishments that we're proud of

Were proud to have been able to join all the different services and idea to create this unique solution. We are also proud to be able to try out new services and learning how they work.

What we learned

The team gained a deeper understanding of the Google Cloud Platform and a stronger understanding of Data Science fundamentals. We also learned much about the financial industry and banking solutions.

What's next for BudgetBuddy

If we were to continue this project next steps would be better layers for automation of the data cycle and more features that track user spending.

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