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Snowflake DAA-C01 Exam Syllabus Topics:

Snowflake SnowPro Advanced: Data Analyst Certification Sample Questions:

1. 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) Run the query against zero-copy clones of the source tables to avoid contention with other queries.
D) Create a materialized view clustered on a date column, on the table that is causing the spilling.

2. A Data Analyst has been asked to predict sales revenue through the end of the year. Which function will provide this information?

A) VARIANCE
B) REGR_SLOPE
C) COVAR_SAMP
D) CORR

3. A Data Analyst needs to create a custom filter called state in a Snowflake dashboard using a SQL query.
Which query will include this custom filter?

A) select avg(total_income), state from taxpayer_wages group by state having state = 'state';
B) select avg(total_income), state from taxpayer_wages group by state having state = :state;
C) select avg(total_income), state from taxpayer_wages group by state having state = state;
D) select avg(total_income), state from taxpayer_wages group by state having state = @state;

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

Solutions: