With which of the following does Oracle Machine Learning allow access to data in Autonomous Database?

Oracle Machine Learning (OML) provides a comprehensive framework for data manipulation and analysis within the Autonomous Database. Its capabilities encompass several key aspects of data handling.

When considering the option that states OML allows access to data through Data Ingestion and Selection, it emphasizes the ability to import and refine datasets for machine learning models, ensuring that relevant data can be selected and prepared for analysis.

Furthermore, the inclusion of Data Viewing and Discovery highlights OML's functionality to explore and visualize data, which is essential for understanding underlying patterns and insights before proceeding to more advanced analyses. This can involve various techniques, such as querying data, generating visualizations, and statistical summarization.

Lastly, the term Data Analysis signifies OML's advanced capabilities to conduct in-depth analyses using machine learning algorithms. This allows users to build, validate, and deploy predictive models based on data housed within the Autonomous Database.

By combining all these aspects—data ingestion, selection, viewing, discovery, and comprehensive data analysis—OML equips users with a powerful suite of tools that facilitate end-to-end data handling. This makes it clear why the option that encompasses all these elements is the most accurate representation of OML's capabilities within the Oracle Autonomous Database context.