DAA-C01 Question #19: Real Exam Question with Answer & Explanation

Question

When working with semi-structured data in Snowflake, how do built-in functions for traversing, flattening, and nesting aid in data manipulation?

Options

• AThey only work with specific file formats
• BThey facilitate handling complex and nested data structures
• CThey limit data transformation possibilities
• DThey restrict data access for user roles

Explanation

Option B is correct because Snowflake's built-in functions - such as FLATTEN, PARSE_JSON, OBJECT_CONSTRUCT, and dot/bracket notation for path traversal - are specifically designed to handle the complexity of nested and hierarchical data (JSON, Avro, Parquet, etc.), enabling you to query, transform, and restructure that data without loading it into a relational schema first.

Why the distractors are wrong:

• A is wrong because these functions work across multiple semi-structured formats (JSON, XML, Avro, ORC, Parquet), not just one.
• C is the opposite of reality - functions like FLATTEN and LATERAL actually expand transformation possibilities by making nested arrays and objects queryable.
• D is a distractor conflating data access control (handled by Snowflake's RBAC/grants system) with data manipulation functions, which have nothing to do with restricting user roles.

Memory tip: Think of the word "FLATTEN" - it's Snowflake's way of unrolling nested structures into rows. If something unfolds complexity, it facilitates handling it (B), not limits it (C/D).

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