SOL-C01 Question #253: Real Exam Question with Answer & Explanation

Question

A data engineer is using Snowflake Notebooks to perform exploratory data analysis on a large dataset stored in a Snowflake table called 'ORDERS. They want to calculate the total order amount per day and visualize the results as a line chart directly within the notebook. Which sequence of actions represents the MOST efficient and correct way to achieve this?

Options

• AWrite a SQL query within the notebook to calculate the total order amount per day, store the result
• BExport the 'ORDERS' table as a CSV file, load it into a separate Python environment, perform the
• CUse the SnowflakeUIto create a view that calculates the total order amount per day, then import
• DWrite a Javascript function within the Snowflake Notebook to fetch the data using fetch API and
• ECreate a stored procedure in Snowflake that calculates the total order amount per day and returns

Explanation

The most efficient approach is to directly query Snowflake from the notebook, use Pandas for data manipulation, and Matplotlib or Plotly for visualization. This leverages the compute power of Snowflake and avoids unnecessary data transfer. Exporting to CSV (B) is inefficient, Javascript (D) isn't the typical notebook flow and stored procedures adds extra complexity (E). Creating a view and importing it (C) adds an extra step compared to directly querying.

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