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

2. A Data Analyst executes a complex query. Which query will allow the Analyst to access the results a second time?

A) SELECT * FROM TABLE(INFORMATION_SCHEMA.QUERY_HISTORY());
B) SELECT LAST_QUERY_ID(-1);
C) DESC RESULT LAST_QUERY_ID();
D) SELECT * FROM TABLE(RESULT_SCAN(LAST_QUERY_ID()));

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 1.2% probability of being included in the sample where repeated elements are allowed.
B) 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.
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. Which Snowflake feature allows users to encapsulate a series of SQL statements into a reusable database object, facilitating modular code development?

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

5. A Data Analyst needs to add address details based on a customer's latitude and longitude to a customer sales database. The Analyst found a free Worldwide Address Data listing on the Snowflake Marketplace. The ACCOUNTADMIN placed the data set into a new database called ADDRESS_DATA. The Data Analyst needs to join the ADDRESS_DATA.OPENADDRESS table with the ORDERS table which is stored in the GLOBAL_DWH database. The combined data set needs to be created as a view. How can this be achieved?

A) Create a view in the GLOBAL_DWH database.
B) Ask the ACCOUNTADMIN to grant the Data Analyst the IMPORTED_PRIVILEGES on the ADDRESS_DATA database and then create a view in the ADDRESS_DATA database.
C) Create a new schema called ENRICHED in the ADDRESS_DATA database and create this view in the ENRICHED schema.
D) Create a view in the ADDRESS_DATA database.

Solutions: