A Data Analyst executes a query in a Snowflake worksheet that returns the total number...

One of the most powerful features of the Snowsight interface for a Data Analyst is the automatic data profiling provided in the results pane. Snowflake automatically calculates statistics and visual distributions for the result set of any query executed in a worksheet, provided the result set is not excessively large.

When the Analyst views the query results, they can simply click on the column header for the "total amount" column. This action opens a summary pane that displays key descriptive statistics such as the mean, sum, and a histogram showing the frequency distribution of the values in that specific column. This allows for immediate visual analysis of data skew, outliers, or common ranges without requiring the analyst to write additional SQL or move the data to an external visualization tool.

Evaluating the Options:

Option A is the Correct answer. This is the fastest, built-in way to perform "exploratory data analysis" (EDA) on a result set within the UI.

Option B and C are incorrect because while Snowsight does have a "Chart" tab, creating a chart requires manual configuration and is a separate step from the automatic profiling features found in the column headers.

Option D is incorrect because calling the WIDTH_BUCKET function would require the Analyst to run the query again with modified SQL logic, which explicitly contradicts the requirements of the question.

This feature significantly enhances the Data Analysis workflow by providing "at-a-glance" insights into data quality and distribution directly within the development environment.