Explanation
About Data Loading: Autonomous Database provides the following loading options: You can load data using Oracle Database Actions. You can load data using Oracle Database tools and Oracle or other 3rd party data integration tools. On transaction processing systems you traditionally ingest data through routine transactions or with DML operations. In general you load data from files local to your client computer or from files stored in a cloud-based object store. To load data from files in the cloud, use either Oracle Database Actions or use the Autonomous Database PL/SQL package DBMS_CLOUD to load files from the cloud. For the fastest data loading experience Oracle recommends uploading the source files to a cloud-based object store, such as Oracle Cloud Infrastructure Object Storage, before loading the data into your database. Oracle provides support for loading files that are located locally in your data center, but when using this method of data loading you should factor in the transmission speeds across the Internet which may be significantly slower. For more information on Oracle Cloud Infrastructure Object Storage, see Putting Data into Object Storage and Overview of Object Storage. Note: If you are not using ADMIN user, ensure the user has the necessary privileges for the operations the user needs to perform. See Manage User Privileges on Autonomous Database - Connecting with a Client Tool for more information.

Explanation
https://docs.oracle.com/en/database/oracle/machine-learning/oml4sql/21/mlsql/oracle-machine-learning-sql-guid

* A false statement regarding Oracle Machine Learning (OML) is that OML offerings need a separate data visualization tool for creating visualization56.
* OML does not need a separate data visualization tool for creating visualization because it provides various options for visualizing data and models within its offerings. For example, OML Notebooks support interactive charts and graphs using Plotly and Matplotlib libraries for Python and R.
OML SQL also supports native SQL functions for creating histograms, scatter plots, box plots, and more

* Contributor is not a type of workspace permission that can be granted to other users in Oracle Machine Learning Notebooks1.
* The types of workspace permissions that can be granted to other users are Manager, Developer, and Viewer1.
* Manager is a user role that allows users to perform all the tasks of a Developer as well as manage other users' workspaces and permissions1.
* Developer is a user role that allows users to create and run notebooks, run SQL statements, create SQL scripts, run Python scripts, create jobs to schedule and run notebooks, use example template notebooks, create and run AutoML experiments, and deploy models1.
* Viewer is a user role that allows users to view notebooks but not run or modify them1

Explanation
https://docs.oracle.com/en/database/oracle/machine-learning/oml-notebooks/omlug/use-library-collaborate-users