Data science is a multidisciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data. In this course, we learned a few key aspects of data science, including data collection and cleaning, exploratory data analysis, machine learning and predictive modelling, and data visualization.

Throughout this class, we used tools and talked about each of those key aspects.

Please elaborate on how each of these steps is related to the next and their relative importance in the whole data science value chain. To answer this question, ask yourself questions like: what is data collection and cleaning for? Could I run an exploratory data analysis exercise before cleaning the data? How effective is data visualization, is it only useful at a specific stage in the process? These questions are non$-$exhaustive and should serve as guides to your reasoning.