Iteration 1: Requirements
Team Noname plans to provide Barrios Technology with a web application that gives users access to predictive modeling and forecasts based on past ISS consumables data. The application's interface will allow users to upload datasets and view flight plans that include analysis of past outcomes and future predictions.
- "Dashboard" home page that presents an overview of relevant data
- Detailed reports on historical usage rates and predictive modeling
- An upload mechanism that allows the user to update the data that analysis and modeling is based on
Predictive Modeling: An algorithm utilizing historical data will predict outcomes based on new client-entered data.
- A browser-based client that uses HTMX or, if necessary, a front-end framework like Svelte to present an interactive dashboard to users.
- A Python-based web server that uses Sanic to handle incoming client requests and route those requests to the necessary predictive modeling and analytics functions.
- Analysis and predictive modeling algorithms that use Python libraries like pandas, dask, and prophet.
- Potentially, a SQL database to store historical data and current analysis and modeling.
- Docker containers will be used to deploy the application to a hosting provider for demonstration purposes. The same containers will be provided to the client with instructions for installation.