Option A:

Incorrect.

• The row with age = NULL fails age >= 75 (NULL comparisons return unknown/false in the WHERE clause).
• The row with country = NULL fails country = 'canada'.
• This output includes rows that violate the WHERE conditions.

Option B:

Incorrect.

• All rows have country = NULL, which does not equal 'canada'.
• The WHERE clause requires country = 'canada', so these rows should be filtered out entirely.

Option C:

Incorrect.

• The query selects only age and country. It does not include the id column.
• Even if the data were correct, the output table structure is wrong.

Option D:

Incorrect.

• The row with age = 14 fails the condition age >= 75.
• The WHERE clause should remove any row where age is less than 75.

Option E:

Correct.

• All rows satisfy both age >= 75 and country = 'canada'.
• Only the requested columns (age and country) are returned.
• No extra columns, no rows with age < 75, and no NULLs that would fail the filter.

Reference Answer

The correct answer is E.

This question tests fundamental SQL concepts:

• How the WHERE clause with AND works (both predicates must be true).
• What columns are actually projected by the SELECT clause.
• Behavior of NULL values in filters (they are excluded).

Mastering these basics is essential for the Databricks Certified Data Analyst - Associate exam, as many questions revolve around correct SQL filtering, projection, and understanding query output structure. Keep practicing similar queries by mentally applying the WHERE conditions to sample data!