Which considerations are part of best practice for ensuring data integrity structures in Snowflake? (Select all that apply)

Question

Options

• AEstablishing parent-child table joins
• BEnsuring data normalization
• CImplementing redundant constraints
• DUsing primary keys for tables

• A
  87% (20)
• B
  4% (1)
• C
  9% (2)

Explanation

Establishing parent-child table joins (A) enforces referential integrity by linking related tables through foreign key relationships, ensuring child records only reference valid parent records. Using primary keys (D) guarantees row uniqueness and prevents duplicate records, which is foundational to maintaining trustworthy data. Together, these two mechanisms form the core of Snowflake's data integrity structures - even though Snowflake doesn't enforce these constraints at write time, defining them communicates intent and enables query optimization.

Data normalization (B) is a database design methodology, not an integrity structure - it reduces redundancy but doesn't directly enforce data accuracy or relationships as a constraint. Redundant constraints (C) are explicitly bad practice: they create conflicting rules, add overhead, and complicate maintenance without any integrity benefit.

Memory tip: Think "PK + FK = integrity" - Primary Keys identify rows, Foreign Keys link parent-child tables. In Snowflake, these are the two pillars of data integrity structure, even though they're metadata-only (unenforced) by default.

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