Manage Semi-Structured and Unstructured Data ARA-C01 Practice Questions (Page 4)

Questions 16–18

1. 16foundation · easy

   Which Snowflake feature is specifically designed to accelerate point lookup queries on semi-structured data?

   • AMaterialized views
   • BSearch optimization
   • CClustering keys
   • DData sharing
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2. 17foundation · easy

   Which Snowflake feature allows you to mask sensitive data in a column at query time based on user roles?

   • AColumn-level security
   • BAccess history
   • CDynamic data masking
   • DRow-level security
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3. 18application · medium

   A developer has a VARIANT column 'data' containing JSON like {"id": 1, "items": [{"sku": "A", "qty": 2}, {"sku": "B", "qty": 3}]}. They need to create a relational table with columns 'id', 'sku', and 'qty', one row per item. Which approach should they use?

   • AUse PARSE_JSON on the entire VARIANT column and then select the fields directly.
   • BUse a SELECT statement with data:items[0].sku to get the first item only.
   • CUse FLATTEN on the 'items' array and then use dot notation to extract the fields, inserting into the target table.
   • DUse OBJECT_CONSTRUCT to build a new object with the 'id' and then use ARRAY_AGG to combine the items.
   Reveal Solution Discussion Select an answer first