Which statement best describes a notebook in Fabric?

• A. It stores data as a physical table only
• B. It is used for interactive data exploration with languages like Python or Spark
• C. It runs only SQL queries with no scripting
• D. It is a data pipeline configuration file

Answer: (B)

Notebooks in Fabric are designed for interactive data exploration with languages like Python or Spark. They provide an interactive workspace where you can write and run code in cells, connect to data sources, perform transformations, and visualize results right alongside code and narrative text. Because you can mix prose, code, and outputs and run code iteratively, notebooks are used for ad hoc analysis and experimentation, not merely for storing data or defining static pipelines. The other descriptions miss this focus: storing data as a physical table is about data storage, whereas notebooks are compute environments; being limited to SQL with no scripting ignores the powerful scripting and programming capabilities; and being a data pipeline configuration file reduces notebooks to a static blueprint, neglecting their interactive and executable nature.