Data Science: Qualitative and Quantitative Analysis

This research project addresses the lack of integration and systematization of data in Ecuador's health sector, a critical issue that limits informed decision-making and service quality. The proposal integrates a multidisciplinary approach combining Big Data, data mining, artificial intelligence, and cybersecurity to process heterogeneous and complex information. The proposed solution is based on the development of distributed cloud architectures and the application of a qualitative and quantitative analysis methodology for software development. Furthermore, the project includes the creation of a virtual laboratory for GNU/Linux practices and the design of training models for identifying cyberattacks based on cognitive factors. As a result, the project expects to strengthen the state of the art in data science, generate indexed scientific publications, and provide practical tools for students and health operators. The impact focuses on the optimization of medical resources, improvements in software development efficiency, and the strengthening of cybersecurity through human behavior modeling.<br/><br/><b>Goal</b>: <br/>Develop a comprehensive data analysis system to systematize information in Ecuador's health sector and optimize distributed software development. The project aims to improve decision-making through Big Data techniques, artificial intelligence, and qualitative-quantitative analysis.<br/><br/><b>Research lines</b>: <br/>Data science and simulation