The data science process

Although every data science project is different, for our illustrative purposes, we can partition an ideal data science project into a series of reduced and simplified phases.

The process starts by obtaining data (a phase know as data ingestion or data acquisition), and as such implies a series of possible alternatives, from simply uploading data to assembling it from RDBMS or NoSQL repositories, or synthetically generating it or scraping it from the web APIs or HTML pages.

Especially when faced with novel challenges, uploading data can reveal itself as a critical part of a data scientist's work. Your data can arrive from multiple sources: databases, CSV or Excel files, raw HTML, images, sound recordings, APIs (https://en.wikipedia.org/wiki/Application_programming_interface) providing JSON files, and so on. Given the wide range of alternatives, we will just briefly touch upon this aspect by offering the basic tools to get your data (even if it is too big) into your...