You are designing a data recovery strategy for a critical table 'CUSTOMER DATA' in your Snowflake environment. The data in this table is highly sensitive, and regulatory requirements mandate a retention period of at least 90 days for potential audits. You need to configure the Time Travel retention period to meet these requirements. What is the maximum supported Time Travel retention period, and how would you set it at the table level?

• A. The maximum retention period is 90 days for Enterprise Edition or higher. You can set it using: 'ALTER TABLE CUSTOMER DATA SET DATA RETENTION TIME IN DAYS = 90;'
• B. The maximum retention period is 90 days. You can set it using: 'ALTER TABLE CUSTOMER_DATA SET = 90;'
• C. The maximum retention period is 365 days. You can set it using: ALTER TABLE CUSTOMER DATA SET DATA RETENTION TIME IN DAYS = 365;'
• D. The maximum retention period depends on your Snowflake edition and can be set at the account level only.
• E. The maximum retention period is 7 days. You can set it using: 'ALTER TABLE CUSTOMER_DATA SET = 7;'

Consider a scenario where you have a Snowflake table named 'CUSTOMER DATA' containing customer IDs (INTEGER) and encrypted credit card numbers (VARCHAR). You need to create a secure JavaScript UDF to decrypt these credit card numbers using a custom encryption key stored securely within Snowflake's internal stage, and then mask all but the last four digits of the decrypted number for data protection. Which of the following actions are necessary to ensure both functionality and security while adhering to Snowflake's best practices for UDF development and security?

• A. Encrypt the key using a weaker encryption algorithm before storing it in an internal stage to balance security and performance.
• B. Pass the encryption key as an argument to the UDF each time it is called.
• C. Use Snowflake's Secure Vault (Secret) feature to store the encryption key and retrieve it securely within the UDF.
• D. Store the encryption key in a separate file on an internal stage accessible only by the UDF's service account and load the key from the file within the UDF at runtime.
• E. Store the encryption key directly within the JavaScript UDF code as a string variable.

You are tasked with optimizing a data pipeline that loads data from an external cloud storage location into Snowflake, transforms it, and then loads it into reporting tables. The pipeline is experiencing intermittent performance issues. You want to proactively identify and address these issues. Which of the following monitoring techniques and Snowflake features would be MOST effective for continuous monitoring and performance optimization?

• A. Rely solely on Snowflake's default query history and resource monitors. These automatically track performance and usage, providing sufficient insight without additional configuration.
• B. Implement custom logging and monitoring using Snowflake Scripting and User-Defined Functions (UDFs) to capture granular performance metrics at each stage of the pipeline and push notifications via external functions to a monitoring service.
• C. Utilize Snowflake's System Functions to periodically query performance views (e.g., 'QUERY_HISTORY, ' and write aggregated metrics to a dedicated monitoring table. Configure a scheduled task to generate alerts based on predefined thresholds.
• D. Focus exclusively on optimizing SQL queries and data transformations. Monitoring is unnecessary since Snowflake automatically handles performance optimization.
• E. Enable Snowflake's Auto-Suspend and Auto-Resume features on the warehouse. This is the most efficient way to manage resources and optimize costs, indirectly addressing performance concerns.

A Snowflake table 'SALES DATA' is frequently updated via Snowpipe. Historical data is occasionally queried using time travel. You notice that time travel queries are becoming increasingly slow. Which of the following Snowflake features or techniques would BEST address this performance degradation?

• A. Create a materialized view that pre-computes the results of common time travel queries.
• B. Implement data clustering on a column that is frequently used in time travel query filters.
• C. Increase the parameter for the 'SALES_DATX table.
• D. Decrease the parameter for the 'SALES_DATA' table.
• E. Periodically clone the ' SALES DATA' table to a separate historical table.

You have a directory table 'my_directory_table' pointing to a stage containing CSV files with headers. You need to query the directory table to find all files modified in the last 24 hours and load those CSV files using COPY INTO into a target table Assume the target table exists and has appropriate schema'. Which of the following SQL statements, or set of statements, will accomplish this efficiently? Note: Consider efficient file loading.

• A.
  
• B.
  
• C.
  
• D.
  
• E.