SnowPro Associate: Platform exam dumps

SnowPro Associate: Platform practice question 265 of 367

SnowPro® Associate: Platform Certification. Associate level, Snowflake. Free question with the correct answer and a full explanation.

SnowPro Associate: Platform Question 265

Single answer● View the table definition

A data engineer needs to confirm the exact column definitions, data types, and nullability for an existing table named SALES in the ANALYTICS.PUBLIC schema before loading a new batch of data. The engineer wants a command that directly returns the table's column metadata from Snowflake. Which statement should they use?

  1. A

    DESCRIBE TABLE ANALYTICS.PUBLIC.SALES;

  2. B

    SHOW TABLES LIKE 'SALES' IN SCHEMA ANALYTICS.PUBLIC;

  3. C

    SELECT * FROM ANALYTICS.PUBLIC.SALES LIMIT 1;

  4. D

    GET_DDL('VIEW', 'ANALYTICS.PUBLIC.SALES');

Show answer and explanation

Correct answer: A

Explanation

To view a table definition in Snowflake, DESCRIBE TABLE is the standard and most direct command for retrieving column-level metadata. It is commonly used by engineers to verify schema details before loading or transforming data. SHOW commands are useful for listing objects and basic properties, but not for full column definitions. A SELECT statement inspects data, not metadata. GET_DDL can also be useful for reviewing how an object was created, but it must reference the correct object type, such as TABLE rather than VIEW. Snowflake documentation for DESCRIBE TABLE and metadata inspection supports using DESCRIBE for this exact use case.

  • A. Correct.

    Correct. DESCRIBE TABLE returns metadata about the table's columns, including column names, data types, nullability, default values, and similar definition details. This is the most direct command for viewing a table definition at the column level in Snowflake.

  • B. Incorrect.

    Incorrect. SHOW TABLES lists table objects and high-level properties such as table name, schema, kind, and retention-related metadata, but it does not return the detailed column-by-column definition needed to validate data types and nullability.

  • C. Incorrect.

    Incorrect. Querying the table with SELECT can show sample data values, but it does not reliably expose the table definition. Inferring data types from returned data is not an appropriate or complete method for confirming the actual schema definition.

  • D. Incorrect.

    Incorrect. GET_DDL can return the DDL used to create an object, but this option specifies the object type as VIEW instead of TABLE. Because SALES is a table in the scenario, this statement is not the correct command as written.

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