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 known as data ingestion). Data ingestion implies a series of possible alternatives, from simply uploading data to assembling it from RDBMS or NoSQL repositories, or from synthetically generating it to scraping it from 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 (if you are clueless about what an API is, you can read a good tutorial about APIs with Python here: https://www.dataquest.io/blog/python-api-tutorial/) providing...
