Snowflake DAA-C01 : SnowPro Advanced: Data Analyst Certification Exam

DAA-C01 real exams

Exam Code: DAA-C01

Exam Name: SnowPro Advanced: Data Analyst Certification Exam

Updated: Oct 03, 2026

Q & A: 67 Questions and Answers

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Snowflake DAA-C01 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Perform Descriptive and Diagnostic Analysis10–15%- Exploratory and ad-hoc analysis
- Statistical summarization and trend analysis
- Anomaly detection and root cause analysis
Topic 2: Prepare and Load Data15–20%- Data ingestion methods: COPY INTO, stages, Snowpipe
- External tables and data validation
- File formats: CSV, JSON, Parquet, Avro
Topic 3: Build and Troubleshoot Advanced SQL Queries20–25%- Complex joins, subqueries, window functions
- Query optimization and troubleshooting
- Semi-structured data processing
Topic 4: Perform Predictive Analysis5–10%- Forecasting and predictive modeling
- Using Snowflake ML and built-in analytics
Topic 5: Use Built-in Functions and Create UDFs10–15%- User-Defined Functions (UDFs)
- Scalar, aggregate, table, system functions
Topic 6: Perform Simple Data Transformations for Analysis15–20%- Handling NULLs and structuring datasets
- Data cleansing, standardization, type conversion
- Views, materialized views, CTEs
Topic 7: Prepare and Present Data10–15%- Align outputs with business requirements
- Data visualization and reporting
- Snowsight dashboards and sharing results

Snowflake SnowPro Advanced: Data Analyst Certification Sample Questions:

Question #1

A Data Analyst is working with a table that has 1 record per day, with sales information. Which window function would calculate a 7-day moving average of sales, where SALES_DATE represents the date column?

  • A. AVG(SALES) OVER (ORDER BY SALES_DATE ROWS BETWEEN 7 PRECEDING AND
    CURRENT ROW)
  • B. SUM(SALES) OVER (ORDER BY SALES_DATE ROWS BETWEEN 6 PRECEDING AND
    CURRENT ROW)
  • C. AVG(SALES) OVER (ORDER BY SALES_DATE ROWS BETWEEN 6 PRECEDING AND
    CURRENT ROW)
  • D. SUM(SALES) OVER (ORDER BY SALES_DATE ROWS BETWEEN 7 PRECEDING AND
    CURRENT ROW)
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

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Question #2

A Data Analyst wants to use pandas code they have previously written to process a column of text and return multiple rows of parsed output for each input value. The Analyst wants to be able to join these results with other tables in a single transaction. Which type of extensibility feature should the Analyst use?

  • A. Stored procedure
  • B. External function
  • C. Vectorized User-Defined Table Function (UDTF)
  • D. User-Defined Function (UDF)
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

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Question #3

What is a benefit of using SQL queries that contain secure views?

  • A. Users will not be able to make observations about the quantity of underlying data.
  • B. Only the number of scanned micro-partitions is exposed, not the number of bytes scanned.
  • C. The amount of data scanned, and the total data volume are obfuscated.
  • D. Snowflake secure views are more performant than regular views.
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

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Question #4

There are two similarly-structured and sized tables, Table_a and Table_b, in a schema with data populated in both tables. A Data Analyst is running queries as part of a preliminary analysis of the data to check the MAX value of a numeric column named num which is present in both the tables:
* Query 1: SELECT MAX(num) FROM Table_a;
* Query 2: SELECT MAX(num) FROM Table_b;
After running the queries, the Analyst observed that Query 2 ran significantly slower than Query 1. Why is this occurring?

  • A. A multi-cluster warehouse was used to run Query 1.
  • B. Table_b has a row-access policy defined.
  • C. Table_b has more rows than Table_a.
  • D. The USE_CACHED_RESULT was set to FALSE before running Query 2.
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

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Question #5

Which Snowflake SQL would a Data Analyst use in a trained Cortex model named forecast_model to retrieve the components that contribute to the predictions?

  • A. forecast_model!SHOW_TRAINING_LOGS()
  • B. forecast_model!SHOW_EVALUATION_METRICS()
  • C. forecast_model!EXPLAIN_FEATURE_IMPORTANCE()
  • D. forecast_model!FORECAST()
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

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