Sofvie Inc. Data Analysis API Project

The main goal of this project is to build API's in Python that connect to a SQL database and help analyze data in various ways. This will involve several different steps for the students, including: - Understanding the existing database structure and data. - Developing API's to access and manipulate data from the database. - Creating algorithms to analyze data in various ways. - Optimizing software runtime performance and assessing areas for improvement. - Researching other variables that can improve the quality of data analysis. - Testing the developed software and making improvements based on additional data.

Health Dashboard in Python/Flask

The project scope entails the development of a Python/Flask application for a health-related purpose, which will include the implementation of various charts. Learners participating in this project will have the opportunity to engage in a real-world application development scenario, focusing on data analysis and visualization within the context of health data. The dataset analysis will aim to provide insightful information that can significantly impact business outcomes and drive strategic decision-making. Throughout the project, learners will gain practical experience in data handling, analysis, and visualization using Python and Flask. They will be tasked with extracting valuable insights from the datasets, identifying trends, patterns, and correlations that could potentially contribute to improving processes and enhancing overall understanding within the health domain. Furthermore, learners will have the opportunity to contribute to the development of the app, implementing charts and visual representations to effectively communicate the findings derived from the dataset analysis. Participation in this project will provide learners with a comprehensive understanding of data analysis methodologies, emphasizing the significance of accurate interpretation and effective communication of findings. Additionally, learners will acquire valuable experience in utilizing Python and Flask for application development in the health sector, which can serve as a solid foundation for future career prospects in the fields of data science, software development, and health technology. The exposure to practical application development within the context of a health-related project will enable learners to refine their skills and foster a deeper understanding of the intersection between data analysis, technology, and healthcare, thereby preparing them to make meaningful contributions in the evolving landscape of the health industry.

Data to map the energy sector

The main goal for the project is to create an analysis of companies involved in the energy sector using publicly available data. The students are expected to collect and organize data from various sources to create a comprehensive map of the energy sector. The outcome of the project should be a detailed analysis of the companies involved in the energy sector. This data will then be used by the data science and marketing teams. This analysis will provide valuable insights for the company, helping it make informed decisions about investments and partnerships in the energy sector.

Strategic data science software development roadmap - features and ideas

The main goal for this project is to develop a strategic data science software development roadmap for Sofvie, a company that specializes in occupational health and safety. The goal is to identify research questions of interest and set a roadmap for the development of future modules. The problem that students will be solving is to determine how the various elements that Sofvie works with can be integrated to support the data science team in their efforts to improve occupational health and safety. This will involve hypothesis testing to see if variables are related and describing ideas for future modules at the intersection of our data (what we can figure out) and helping build future development plans. This roadmap will include specific modules and features that can be implemented in the future, and will be based on research questions of interest and the integration of various elements that Sofvie works with.