SQL ( Structured Query Language ) is Needed for Data Scientists to get the data and to work with that data. Everyone is busy to Learn R or Python for Data Science, but without Database Data Science is meaningless. Machine learning is enabling computers to tackle tasks that have, until now, only been carried out by people. From driving cars to translating speech, machine learning is driving an explosion in the capabilities of artificial intelligence --helping software make sense of the messy and unpredictable real world.
Finer words never spoken. There are a whole l of people that just don't get that. People also need to understand that a "Database" does not have to be a relational database for to use ML but having a strong understanding of relational databases will help a whole lot.
See this https://colab.research.google.com/
Sometimes, you might not necessarily need a Database in ML hence no need for Structured Query Language. In the above example of Machine Learning Translation, you can leverage delimited and compressed files. But it does help greatly to have some depth of knowledge of databases
A "database" doesn't necessarily mean something that you need SQL for. A simple file is actually classified as a "database", even a relatively unstructured file.
Indeed. Like dna or cell