We already discussed in detail the various steps involved in a typical data science project separately in different chapters. Let us quickly glance through what we have covered already and touch upon some important aspects. A high-level overview of the steps involved may appear as in the following figure:

In the preceding pictorial representation, we have tried to explain the steps involved in a data science project at a higher level, mostly generic to many data science assignments. Many more substeps are actually present at every stage, but may differ from project to project.

It is very difficult for data scientists to find the best approach and steps to follow in the beginning. Generally, data science projects do not have a well-defined life cycle such as the Software Development Life Cycle (SDLC). It is usually the case that data science projects get tramped into delivery delays with repeated hold-ups, as most of the steps in the life cycle are iterative. Also, there could...