SnowPro Core Certification Exam Questions and Answers
Question 165
What is a machine learning and data science partner within the Snowflake Partner Ecosystem?
Options:
A.
Informatica
B.
Power Bl
C.
Adobe
D.
Data Robot
Answer:
D
Explanation:
Data Robot is recognized as a machine learning and data science partner within the Snowflake Partner Ecosystem. It provides an enterprise AI platform that enables users to build and deploy accurate predictive models quickly. As a partner, Data Robot integrates with Snowflake to enhance data science capabilities2.
[References:, [COF-C02] SnowPro Core Certification Exam Study Guide, Snowflake Documentation on Machine Learning & Data Science Partners, , https://docs.snowflake.com/en/user-guide/ecosystem-analytics.html, , ]
Question 166
What is the default character set used when loading CSV files into Snowflake?
Options:
A.
UTF-8
B.
UTF-16
C.
ISO S859-1
D.
ANSI_X3.A
Answer:
A
Explanation:
For delimited files (CSV, TSV, etc.), the default character set is UTF-8. To use any other characters sets, you must explicitly specify the encoding to use for loading. For the list of supported character sets, see Supported Character Sets for Delimited Files (in this topic).
Question 167
Which of the following can be executed/called with Snowpipe?
Options:
A.
A User Defined Function (UDF)
B.
A stored procedure
C.
A single copy_into statement
D.
A single insert__into statement
Answer:
C
Explanation:
Snowpipe is used for continuous, automated data loading into Snowflake. It uses a COPY INTO
statement within a pipe object to load data from files as soon as they are available in a stage. Snowpipe does not execute UDFs, stored procedures, or insert statements. References: Snowpipe | Snowflake Documentation
Question 168
What feature can be used to reorganize a very large table on one or more columns?
Options:
A.
Micro-partitions
B.
Clustering keys
C.
Key partitions
D.
Clustered partitions
Answer:
B
Explanation:
Clustering keys in Snowflake are used to reorganize large tables based on one or more columns. This feature optimizes the arrangement of data within micro-partitions to improve query performance, especially for large tables where efficient data retrieval is crucial. References: [COF-C02] SnowPro Core Certification Exam Study Guide
