Snowflake SnowPro Advanced DAA-C01

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Snowflake DAA-C01 Exam Syllabus Topics:

Snowflake SnowPro Advanced: Data Analyst Certification Sample Questions:

1. 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) Snowflake secure views are more performant than regular views.
D) The amount of data scanned, and the total data volume are obfuscated.

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

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

4. A Data Analyst has created a custom filter called branch_region on a Snowflake dashboard. The filter contains a list of regions where the company has stores. How should the filter be referenced in dashboard queries?

A) %branch_region
B) $branch_region
C) ::branch_region
D) :branch_region

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) Run the query against zero-copy clones of the source tables to avoid contention with other queries.
B) Create a materialized view clustered on a date column, on the table that is causing the spilling.
C) Split the query into multiple steps, replacing Common Table Expressions (CTEs) with temporary tables to process the data in smaller batches.
D) Change the source tables into external tables to establish and take advantage of custom partitioning.

Solutions: