For most real-world projects, there is some defined sequence of steps to be followed. However, there are no universally agreed upon definitions or boundaries for data analytics and data science. Generally, the term "data analytics" encompasses the techniques and processes involved in examining data, discovering useful insights, and communicating them. The term "data science" can be best treated as an interdisciplinary field drawing from statistics, computer science, and mathematics. Both terms deal with processing raw data to derive knowledge or insights, usually in an iterative fashion, and some people use them interchangeably.
Based on diverse business requirements, there are different ways of approaching problems but there is no unique standard process that fits in well with all possible scenarios. A typical process workflow can be summarized as a cycle of formulating a question, exploring, hypothesizing, validating the hypothesis, analyzing the results, and starting...