What actions are involved in data discovery to identify necessary elements from available datasets in Snowflake? (Select all that apply)

Question

Options

• ARunning SQL queries on tables
• BEvaluating necessary transformations
• CPerforming data mining techniques
• DIdentifying missing data fields

• A
  89% (51)
• C
  7% (4)
• D
  4% (2)

Explanation

Data discovery in Snowflake centers on understanding what data is available and what work is needed to use it effectively. Running SQL queries (A) is a core discovery action - it lets you inspect table schemas, sample records, and understand data distributions directly within Snowflake. Evaluating necessary transformations (B) is equally essential because once you've identified available data, you must assess what cleaning, joining, or reshaping is required before it can serve its intended purpose.

C is incorrect because data mining is a separate, more advanced analytical discipline (pattern detection, predictive modeling) that occurs after discovery and preparation - not during it. D is incorrect because identifying missing fields is a data quality assessment concern; discovery focuses on cataloging what exists in available datasets, not auditing for gaps.

Memory tip: Think of data discovery as two verbs - "find it" (SQL queries) and "plan for it" (transformation evaluation). Mining and gap analysis belong to later pipeline stages, not the discovery phase.

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