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Snowflake Certified SnowPro Associate - Platform Certification Sample Questions:

1. You have a Python script that uses Snowpark to connect to Snowflake. You want to ensure that the connection parameters, such as account identifier, username, password, and database, are securely managed and not hardcoded directly in the script. Which of the following strategies would be most effective and secure for managing these sensitive connection parameters?
Choose all that apply:

A) Use Snowflake's Secret object to store credentials, and use Snowpark to retrieve these secrets for connection.
B) Hardcode the parameters within the Python script, but obfuscate them using Base64 encoding.
C) Store the connection parameters in a configuration file encrypted with a strong encryption algorithm, and decrypt it within the Python script using a key stored separately and securely.
D) Utilize environment variables to store the connection parameters and access them from the Python script.
E) Store the connection parameters in a plain text file in a secure location on the server.

2. You have been tasked with configuring a session parameter for all users connecting to a specific Snowflake database named REPORTING DB'. You want to set the 'TIMEZONE parameter to
'America/Los_Angeles' for all sessions within this database. Which of the following SQL statements would BEST accomplish this?

A) ALTER USER SET TIMEZONE = 'America/Los_Angeles';
B) ALTER ACCOUNT SET TIMEZONE = 'America/Los_Angeles';
C) ALTER WAREHOUSE SET TIMEZONE = 'America/Los_Angeles';
D) ALTER SESSION SET TIMEZONE = 'America/Los_Angeles';
E) ALTER DATABASE REPORTING_DB SET TIMEZONE = 'America/Los_Angeles';

3. A company stores unstructured text data (PDFs, DOCX) in an external stage (AWS S3). They want to use Snowflake Cortex's PARSE DOCUMENT function to extract specific information, but are encountering performance issues and high costs. Which of the following strategies could optimize performance and reduce costs when using PARSE DOCUMENT in this scenario?

A) Implement a robust error handling mechanism to prevent processing from halting due to malformed or corrupted documents and monitor the Snowflake resource consumption using Snowflake's monitoring tools.
B) Reduce the number of documents being processed in a single batch to minimize memory consumption.
C) Pre-process the documents to remove irrelevant sections (e.g., boilerplate text, headers, footers) before loading them into Snowflake for parsing. Also, ensure appropriate partitioning of data in the external stage.
D) Utilize Snowflake's caching mechanism by storing parsed results in a separate table and refreshing it periodically, avoiding redundant parsing of the same documents and reduce MAX FILE SIZE to lower value like 'MAX FILE SIZE-8388608'.
E) Increase the size of the virtual warehouse used for processing, even if it means paying for larger compute resources, and use 'MAX in the file format configuration.

4. A data scientist wants to use the COMPLETE function in Snowflake Cortex to perform sentiment analysis on social media posts. They have a table named 'SOCIAL MEDIA POSTS with a column
'POST TEXT' containing the post content. They want to classify each post as either 'Positive',
'Negative', or 'Neutral'. Which of the following SQL statements is the MOST appropriate for this task?

A) Option B
B) Option E
C) Option D
D) Option C
E) Option A

5. What MOST accurately describes Snowflake?

A) A transactional database
B) A data warehouse software
C) An ETL tool
D) An AI data cloud platform

Solutions: