DAA-C01 sample questions

Question 1

A quantitative analyst at a hedge fund needs to align a table of executed stock trades with a table of quote prices. The requirement is to find the prevailing bid price at the exact moment or immediately before a trade occurred. The timestamps will rarely match exactly. Which approach is the most efficient and semantically correct in Snowflake?

Accepted Answer

Use an ASOF JOIN matching on the stock symbol and the timestamp.

Answer

Use a LEFT JOIN with a BETWEEN condition and an aggregate function.

Answer

Use a CROSS JOIN combined with a QUALIFY clause.

Answer

Use an INNER JOIN with a LATERAL subquery that orders by timestamp.

Question 2

A data engineer is loading millions of records from JSON files into Snowflake using the COPY INTO command. They anticipate that approximately 5% of the records will have schema mismatches or corrupt formatting. They want to load all valid records, skip the invalid ones, and capture the errors for later review without failing the entire load operation. Which TWO actions should they take? (Select TWO)

Accepted Answer

Set ON_ERROR = CONTINUE in the COPY INTO statement.

Accepted Answer

Query the VALIDATE table function to review the specific errors after the load.

Answer

Set ON_ERROR = SKIP_FILE in the COPY INTO statement.

Answer

Query the COPY_HISTORY view to see the exact row-level data that failed.

Answer

Set ERROR_ON_COLUMN_COUNT_MISMATCH = FALSE in the file format.

Question 3

The GENERATOR table function in Snowflake requires an existing physical table to produce synthetic rows.

Accepted Answer

False

Answer

True

Question 4

A healthcare provider wants to share an anonymized patient outcome dataset exclusively with three specific research universities. They require strict control over who can discover the listing and consume the data to comply with regulations. Which Snowflake sharing mechanism should they use?

Accepted Answer

Private Listing

Answer

Snowflake Marketplace Public Listing

Answer

Internal Marketplace

Answer

Unmanaged Direct Share

Question 5

A data engineering team at a retail company manages a complex data ingestion pipeline. Data lands in an external S3 stage, is loaded into raw tables via Snowpipe, and is transformed downstream using a series of Tasks and Streams.

Recently, PII data was discovered in a downstream aggregate table where it should not exist. The security team needs to audit exactly which users queried the raw and aggregate tables over the last 30 days. Simultaneously, the data analysts need to trace how the PII column propagated from the raw table through the intermediate tables to the aggregate table.

Which combination of Snowflake features provides the natively built-in solution for these requirements?

Accepted Answer

Use ACCESS_HISTORY for access auditing and OBJECT_DEPENDENCIES for lineage.

Answer

Use QUERY_HISTORY for access auditing and DATA_METRIC_FUNCTIONS for lineage.

Answer

Use LOGIN_HISTORY for access auditing and TAG_REFERENCES for lineage.

Answer

Use COPY_HISTORY for access auditing and STREAMS for lineage.

Question 6

A data architect is designing a schema for a BI tool that heavily relies on join culling to improve performance. How should they configure PRIMARY KEY and FOREIGN KEY constraints in Snowflake to ensure the query optimizer utilizes them?

Accepted Answer

Define the constraints with the RELY property so the optimizer expects the data to comply.

Answer

Create standard PRIMARY KEY and FOREIGN KEY constraints, as they are enforced by default.

Answer

Use the ENFORCE keyword when creating the constraints.

Answer

Constraints in Snowflake are strictly for documentation and cannot be used by the optimizer.

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Free DAA-C01 sample questions

The GENERATOR table function in Snowflake requires an existing physical table to produce synthetic rows.

A healthcare provider wants to share an anonymized patient outcome dataset exclusively with three specific research universities. They require strict control over who can discover the listing and consume the data to comply with regulations. Which Snowflake sharing mechanism should they use?

A data architect is designing a schema for a BI tool that heavily relies on join culling to improve performance. How should they configure PRIMARY KEY and FOREIGN KEY constraints in Snowflake to ensure the query optimizer utilizes them?

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