COF-C03 Question 120
Single answerSnowflake NotebooksA data analyst wants to use a Snowflake Notebook to explore sales data, run SQL and Python cells in the same notebook, and share the notebook with teammates who should be able to rerun it against the same database objects. The analyst also wants to minimize setup outside Snowflake. Which action should the analyst take FIRST to meet these requirements?
- A
Create and select a warehouse that the notebook can use for compute, then create the notebook in a database schema
- B
Export the notebook to a local Jupyter environment because Snowflake Notebooks cannot mix SQL and Python in one notebook
- C
Create a Snowpark Container Services service because every Snowflake Notebook requires containers before it can run cells
- D
Create a stage and upload a .ipynb file because notebooks in Snowflake can only be created by importing an external notebook file
Show answer and explanation
Correct answer: A
Explanation
The best first step is to ensure compute is available and then create the notebook as a Snowflake object in a schema. Snowflake Notebooks are designed to let users work directly in Snowflake with languages such as SQL and Python, reducing dependence on external environments. Because notebooks are stored within Snowflake, sharing and collaboration are governed by standard Snowflake object access patterns and privileges on the notebook, schema, database, warehouse, and underlying data objects. This makes option 1 the only answer that satisfies all stated requirements: mixed-language analysis, rerun capability for teammates, and minimal setup outside Snowflake. This is consistent with Snowflake documentation describing notebooks as schema-level objects that run using Snowflake compute and support integrated data exploration and development workflows.
- A. Correct.
Correct. Snowflake Notebooks are created as objects in a schema and use Snowflake compute to run cells. To execute SQL and Python in the notebook, the user needs an available compute resource such as a warehouse. This aligns with the requirement to keep work inside Snowflake and allow teammates with the right permissions to access the same notebook object and underlying database objects.
- B. Incorrect.
Incorrect. Snowflake Notebooks support multiple languages, including SQL and Python, within the same notebook experience. Exporting to local Jupyter would increase setup outside Snowflake, which is the opposite of the stated goal.
- C. Incorrect.
Incorrect. Snowpark Container Services is not a prerequisite for standard use of Snowflake Notebooks. A candidate might choose this option because notebooks can be associated with advanced runtime capabilities in some scenarios, but core notebook usage for SQL and Python analysis does not require creating a container service first.
- D. Incorrect.
Incorrect. Snowflake Notebooks do not have to be created only by importing an external .ipynb file. A user can create a notebook directly in Snowflake. This option reflects a common misconception based on experience with external notebook tools.