Snowflake DAA-C01 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Data Loading and Unloading | - Data ingestion methods
|
| Snowflake Architecture and Data Platform Fundamentals | - Data platform fundamentals
|
| Data Modeling and Performance Optimization | - Performance tuning
|
| Data Transformation and Analysis | - SQL-based transformations
|
| Security, Governance, and Data Sharing | - Access control and security
|
Snowflake SnowPro Advanced: Data Analyst Certification Sample Questions:
1. What option would allow a Data Analyst to efficiently estimate cardinality on a data set that contains trillions of rows?
A) SYSTEM$ESTIMATE
B) Count(Distinct *)/Count(*)
C) HLL(*)
D) Count(Distinct *)
2. A Data Analyst executes a query in a Snowflake worksheet that returns the total number of daily sales, and the total amount for each sale. How can the Analyst check the distribution of the total amount, without running the query again?
A) Go to Chart and select a bar chart that contains the two variables.
B) Click on the column header in the results and review the histogram.
C) Go to Chart and select a histogram that includes the two variables.
D) Call the WIDTH_BUCKET function.
3. When sharing views across accounts, which function should be used on the row access policy for the secure views to give users access to rows in a base table?
A) CURRENT_ROLE
B) CURRENT_USER
C) CURRENT_AVAILABLE_ROLES
D) CURRENT_ACCOUNT
4. A scorecard tile on a Snowsight dashboard shows a comparison between the industry average employee age (which is 34) and a company's average employee age (which is 38). The scorecard tile looks like this:
Comparison with industry average
How should this tile be interpreted?
A) 38 is the value and 12% is the standard deviation.
B) 38 is the value and 12% is the percent difference from the comparison.
C) 38 is the comparison and 12% is the average age change in the last year.
D) 38 is the comparison and 12% is the projected industry growth.
5. A large, complicated query is used to generate a data set for a report on the most recent month. It is taking longer than expected. A review of the Query Profile shows excessive spilling. How can the performance of the query be improved WITHOUT increasing costs?
A) Change the source tables into external tables to establish and take advantage of custom partitioning.
B) Split the query into multiple steps, replacing Common Table Expressions (CTEs) with temporary tables to process the data in smaller batches.
C) Create a materialized view clustered on a date column, on the table that is causing the spilling.
D) Run the query against zero-copy clones of the source tables to avoid contention with other queries.
Solutions:
| Question # 1 Answer: C | Question # 2 Answer: B | Question # 3 Answer: D | Question # 4 Answer: B | Question # 5 Answer: B |
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