Data Science and Data Analytics are two distinct fields, though they overlap in many areas. Data Science is a broader field that includes various techniques such as machine learning, predictive modeling, and statistics. It involves extracting insights from various forms of data, both structured and unstructured. Data Science is more focused on designing and constructing new processes for data modeling and production using prototypes, algorithms, predictive models, and custom analysis. On the other hand, Data Analytics is more focused on processing and performing statistical analysis on existing datasets. It is used to discover useful information and aid in business decision making. Data Analytics tends to be more business and process-oriented. In summary, while both fields involve working with data, the main difference lies in the scope and focus of what they do with this data.