To access the Research division data for Productline1 in a notebook, which syntax is correct?

The correct option for accessing the Research division data for Productline1 in a notebook is to use the SQL syntax provided in the first choice. This approach leverages the Spark SQL capabilities, allowing for a simple and expressive way to query the data stored in a structured format, such as a Delta table.

Using the command spark.sql("SELECT * FROM Lakehouse1.ResearchProduct") indicates that we are requesting to select all columns from the specified table, which resides within the Lakehouse architecture. The clear naming of the data source ("Lakehouse1.ResearchProduct") implies proper organization and accessibility of the data, showcasing a well-structured data lake environment where data can be queried with SQL-like syntax.

The other options represent different methods of data access but may not be suitable for retrieving the specific data in the requested way. For example, one option suggests a Delta format load, which would be appropriate for reading data but does not inherently provide a way to run a SQL query directly. Another option uses a command more typical in a non-Spark context, and the last one lacks the proper syntax to specify or clearly identify the dataset in question, thus making them less aligned with the requirements of the scenario provided.