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SnowPro Advanced: Data Analyst Free Sample Questions

Description

Covers data ingestion and discovery from the Snowflake Marketplace, preparing and cleaning data, descriptive and diagnostic analysis with SQL, and building and maintaining reports and dashboards.

12 free sample questions150 in the full practice test

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DAA-C01 Sample Questions

  1. Question 1

    Advanced

    Data Ingestion and Data Preparation · Query tables to assess data and required transformations

    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?

    Answer and explanation

    Correct answer: A

    An ASOF JOIN is specifically designed for time-series analysis where you need to join records based on the closest preceding (or exact) timestamp. It is highly optimized for this exact scenario, avoiding the massive performance overhead of a CROSS JOIN or complex window functions.

    flowchart TD A[Trades Table] -->|Timestamp matching| B{ASOF JOIN} C[Quotes Table] -->|Most recent prior| B B --> D[Enriched Trade Data]

  2. Question 2

    IntermediateMultiple answers

    Data Ingestion and Data Preparation · Load data and perform DML

    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)

    Answer and explanation

    Correct answers: B, C

    The VALIDATE table function is used to view all errors encountered during a previous execution of the COPY command, allowing the engineer to review the skipped records.

    Setting ON_ERROR = CONTINUE instructs the COPY command to continue loading valid records even if it encounters errors in some rows.

  3. Question 3

    Beginner

    Data Ingestion and Data Preparation · Retrieve data from a source

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

    Answer and explanation

    Correct answer: B

    False. The GENERATOR function creates rows of synthetic data natively based on the ROWCOUNT or TIMELIMIT parameters. It does not require an underlying physical table, making it ideal for generating test datasets efficiently.

  4. Question 4

    Intermediate

    Data Ingestion and Data Preparation · Use Secure Data Sharing to enrich existing data sets

    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?

    Answer and explanation

    Correct answer: D

    Private Listings allow a provider to share data directly with specific Snowflake accounts. The listing is not visible on the public Snowflake Marketplace, providing the strict control required for sensitive healthcare data.

  5. Question 5

    Advanced

    Data Ingestion and Data Preparation · Automate pipelines and respond to failures

    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?

    flowchart LR A[S3 Stage] -->|Snowpipe| B[Raw Table] B -->|Task/Stream| C[Intermediate Table] C -->|Task/Stream| D[Aggregate Table]
    Answer and explanation

    Correct answer: D

    ACCESS_HISTORY is the native Snowflake view used to audit which users accessed what data (including reads and writes). OBJECT_DEPENDENCIES is the native view used to track data lineage, showing how objects like tables and views depend on one another, enabling analysts to trace the PII propagation.

  6. Question 6

    Beginner

    Data Ingestion and Data Preparation · Keys, joins, and constraints

    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?

    Answer and explanation

    Correct answer: B

    In Snowflake, primary and foreign key constraints (except NOT NULL) are informational and not enforced. However, if the data is known to be clean, setting the RELY property on the constraint tells the Snowflake optimizer to assume the constraint is valid, enabling advanced optimizations like join culling.

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