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Snowflake DAA-C01 Braindumps - in .pdf Free Demo

  • Exam Code: DAA-C01
  • Exam Name: SnowPro Advanced: Data Analyst Certification Exam
  • Last Updated: Aug 20, 2026
  • Q & A: 67 Questions and Answers
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  • PDF Price: $59.98    

Snowflake DAA-C01 Braindumps - Testing Engine PC Screenshot

  • Exam Code: DAA-C01
  • Exam Name: SnowPro Advanced: Data Analyst Certification Exam
  • Last Updated: Aug 20, 2026
  • Q & A: 67 Questions and Answers
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Snowflake DAA-C01 Exam Syllabus Topics:

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

Snowflake SnowPro Advanced: Data Analyst Certification Sample Questions:

1. A Data Analyst created two functions and one procedures:
The Analyst then runs this query:

The Analyst then runs this query:

What will be the output?

A) 30
B) Null
C) 20
D) 10


2. A Data Analyst for a ride-sharing company needs to assess the relationship between the number of active drivers in a city, and the average waiting time for passengers. Which query will determine if an increase in the number of active drivers is associated with a decrease in the average waiting time?

A) SELECT CITY, CORR(ACTIVE_DRIVERS, AVERAGE_WAITING_TIME) FROM RIDE_DATA GROUP BY CITY;
B) SELECT CITY, SUM(ACTIVE_DRIVERS), VARIANCE(AVERAGE_WAITING_TIME) FROM RIDE_DATA GROUP BY CITY;
C) SELECT CITY, VARIANCE(ACTIVE_DRIVERS, AVERAGE_WAITING_TIME) FROM
RIDE_DATA GROUP BY CITY;
D) SELECT CITY, SUM(ACTIVE_DRIVERS), AVG(AVERAGE_WAITING_TIME) FROM
RIDE_DATA GROUP BY CITY;


3. What will the following query return?
SELECT * FROM testtable SAMPLE BLOCK (0.012) REPEATABLE (99992);

A) A sample of a table in which each block of rows has a 0.012% probability of being included in the sample, with the seed set to 99992.
B) A sample of a table in which each block of rows has a 1.2% probability of being included in the sample where repeated elements are allowed.
C) A sample of a table in which each block of rows has a 1.2% probability of being included in the sample, with the seed set to 99992.
D) A sample containing 99992 records of a table in which each block of rows has a 0.012% probability of being included in the sample.


4. A Data Analyst is working with three tables:

Which query would return a list of all brokers, a count of the customers each broker has. and the total order amount of their customers (as shown below)?

A)

B)

C)

D)


5. 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) User-Defined Function (UDF)
B) External function
C) Stored procedure
D) Vectorized User-Defined Table Function (UDTF)


Solutions:

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

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