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

"SnowPro Advanced: Data Analyst Certification Exam", also known as DAA-C01 exam, is a Snowflake Certification. With the complete collection of questions and answers, PrepAwayPDF has assembled to take you through 67 Q&As to your DAA-C01 Exam preparation. In the DAA-C01 exam resources, you will cover every field and category in SnowPro Advanced Certification helping to ready you for your successful Snowflake Certification.

  • Exam Code: DAA-C01
  • Exam Name: SnowPro Advanced: Data Analyst Certification Exam
  • Certification Provider: Snowflake
  • Corresponding Certification: SnowPro Advanced
  • Updated: Aug 10, 2026
  • No. of Questions: 67 Questions & Answers with Testing Engine
  • Download Limit: Unlimited

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Snowflake DAA-C01 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Data Presentation and Data Visualization28%-29%- Create dashboards
  • 1. Snowsight dashboards
  • 2. Present analytical results
- Integrate with BI tools
  • 1. Power BI integration
  • 2. Other partner visualization tools
  • 3. Tableau integration
Topic 2: Data Analysis30%-32%- Perform advanced analytics using SQL
  • 1. Time-series analysis
  • 2. Snowflake-specific analytical features
  • 3. Aggregate functions
Topic 3: Data Ingestion and Data Preparation15%-20%- Prepare data and load into Snowflake
  • 1. Load data from external/internal stages into a table
  • 2. Load files using Snowsight
- Enrich data by identifying and accessing relevant data from the Snowflake Marketplace
  • 1. Use Secure Data Sharing (Marketplace, Internal Marketplace, Private Listings, Listings)
  • 2. Create tables and views
  • 3. Find external data sets that correlate with available data
- Implement data processing solutions
  • 1. Cleanse, conform, and enrich data
  • 2. Automate and implement data pipelines (scheduling)
  • 3. Respond to processing failures
  • 4. Use logging and monitoring solutions (auditing, data lineage)
- Use best practice considerations relating to data integrity structures
  • 1. Perform table joins between parent/child tables
  • 2. Implement constraints
  • 3. Define primary keys for tables
- Use a collection system to retrieve data
  • 1. Retrieve data from structured sources (CSV)
  • 2. Retrieve data from semi-structured sources (Parquet, Avro, ORC, JSON, XML)
  • 3. Synthetic Data Generation
  • 4. Retrieve data from unstructured sources
- Perform data discovery to identify what is needed from available datasets
  • 1. Use commands to read metadata or alter context (DESCRIBE, SHOW, USE)
  • 2. Determine the level of data granularity required
  • 3. Evaluate required transformations (table joins, set operations, ASOF JOINS)
  • 4. Query tables to assess data elements and statistics maintained by Snowflake
  • 5. Identify elements required for business goals using BI reports or SQL analysis
Topic 4: Data Transformation and Data Modeling22%-30%- Transform data using SQL
  • 1. Window functions
  • 2. QUALIFY clauses
  • 3. Common Table Expressions (CTEs)
  • 4. PIVOT/UNPIVOT operations
- Design data models
  • 1. Snowflake schema design
  • 2. Data vault models
  • 3. Star schema design

Snowflake SnowPro Advanced: Data Analyst Certification Sample Questions:

1. A Data Analyst created a model called modelX using SNOWFLAKE.ML.FORECAST. The Analyst needs to predict the next few values and save the result directly into tableX. What step does the Analyst need to take after calling the modelX!FORECAST function?

A) Load the function call results directly INTO tableX.
B) List the cache content, then use the data saved in the RESULT_SCAN for tableX.
C) Create the table by querying the RESULT_SCAN.
D) Pass the new table as a function argument.


2. A Data Analyst created a cost overview dashboard in Snowsight. Management has asked for a system date filter to easily change the time period and refresh the data in all dashboard tiles with a single filter selection.
The system date filter is shown below:

The Analyst wants to apply the filter onto individual dashboard components.
Adding which where clause to the queries will apply the filter as required?

A) Where start_time = :date_filter
B) Where start_time = :daterange
C) Where start_time >= dateadd('days', -7, SYSDATE())
D) Where start_time >= dateadd('days', -7, CURRENT_TIMESTAMP())


3. A Data Analyst runs this query:

The Analyst men runs this query:

What will be the output?

A)

B)

C)

D)


4. Which Snowflake feature allows users to encapsulate a series of SQL statements into a reusable database object, facilitating modular code development?

A) Stored procedure
B) User-Defined Function (UDF)
C) Materialized view
D) Common Table Expressions (CTE)


5. This query is run:
SQL
SELECT
customer.id,
ANY_VALUE(customer.name),
SUM(orders.value)
FROM customer
JOIN orders ON customer.id = orders.customer_id
GROUP BY customer.id;
What is the effect of ANY_VALUE in this syntax?

A) It will return some value of the expression from the group, with a non-deterministic result.
B) It will return an equivalent NULL value when the expression is evaluated.
C) It will return the minimum value of those generated by the expression, with a deterministic result.
D) It will return a value equivalent to the median of those generated by the expression, which may be a non-deterministic result.


Solutions:

Question # 1
Answer: C
Question # 2
Answer: B
Question # 3
Answer: C
Question # 4
Answer: A
Question # 5
Answer: A

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