CloudSibyl is seeking to enhance its user experience by developing a recommendation system based on its existing data model. The goal of this project is to create a system that can analyze user data and provide personalized content recommendations. This project will allow learners to apply their knowledge of data analysis, machine learning, and software development to build a functional recommendation engine. The team will work with CloudSibyl's existing data sets, utilizing algorithms to identify patterns and trends that can inform the recommendation process. By the end of the project, learners will have gained practical experience in developing a recommendation system, which is a valuable skill in the tech industry.

- Understand CloudSibyl's current data model and user data.

- Research and select appropriate algorithms for recommendation systems.

- Develop and test a prototype recommendation engine.

- Analyze the effectiveness of the recommendations and refine the system.

The project deliverables will include a functional prototype of a recommendation system tailored to CloudSibyl's needs. Additionally, the team will provide a comprehensive report detailing the algorithms used, the development process, and the system's performance. This report will also include recommendations for future improvements and scalability.

- A working prototype of the recommendation system.

- A detailed report on the development process and system performance.

- Recommendations for future enhancements and scalability.