Why do we need data scientists if there are websites like this?
Without having a complete knowledge of the features on that website I would say:

Data visualization is only one part on data scientist (ds) pipeline from data understanding thought model validation and model production as per CRISP-DM, and that site seems to be focused on that.

Introductory courses on data science most of the time work with &quot;ready to use&quot; data frames (Iris, Titanic) that do not reflect the real way in which data must be preprocessed and aggregated to the correct level (ex. you may have accounts level data that needs to be aggregated to user's level to predict user's default) also, in many cases you have multiple sources of data stored in a variety of places like relation tables or non structured information that will need to be queried and joined beforehand.


The latter role is commonly attributed as a &quot;data engineer&quot;, however in small to medium projects the line between the two roles are less discernible. It is important to note, however, that this line should be fuzzy, as more often than not choices made by data scientists require work from a data engineering perspective, - as other answers below have touched more upon.
And this gives a wrong impression of simplicity on the task.
Besides, the above step would need for you to have at least basic understanding of the data you are working on in order to create &quot;meaningful&quot; features that otherwise will end just by aggregating by min, max and average (sometimes useful but not sufficient)

Finally, a trained model in a notebook would hardly being helpful if you cannot use that model in an completely deployed way (having a AWS lambda for example)