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Snowflake NAS-C01 Exam Syllabus Topics:

Snowflake SnowPro Specialty - Native Apps Sample Questions:

1. You're developing a Snowflake Native Application that performs complex data transformations within the consumer's account. These transformations require substantial compute resources. You want to optimize resource utilization and minimize cost for your consumers.
Which strategies can you employ to achieve this goal? (Select TWO)

A) Do not use transactions for data transformation pipelines as transactions introduce overhead.
B) Implement data skipping techniques to minimize the amount of data scanned during transformations. This involves clustering tables appropriately.
C) Utilize Snowflake's auto-suspend and auto-resume features for virtual warehouses to minimize compute costs when the application is idle.
D) Implement dynamic scaling by programmatically adjusting the virtual warehouse size based on the workload using stored procedures and the function to cancel long running and inefficient tasks.
E) Force consumers to use the largest possible virtual warehouse size to ensure transformations complete quickly.

2. You are developing a Snowflake Native Application and want to implement robust observability and telemetry. Which of the following approaches will enable you to effectively monitor the application's performance, identify errors, and collect usage metrics within the consumer's account?

A) Directly access the consumer's system tables (e.g., 'SNOWFLAKE.ACCOUNT USAGE.QUERY HISTORY) to extract application-related metrics based on query identifiers generated by the application.
B) Utilize to write log data to a secure table within the application and leverage views granted to the consumer to expose relevant metrics and error information. Ensure appropriate roles have access to the views.
C) Implement custom logging using 'SYSTEM$LOG' and store application logs in a separate table within the application's container. Configure grants to allow the application developer to access these logs.
D) Rely solely on Snowflake's built-in query history and resource monitoring features in the consumer's account, as these automatically capture all application activity.
E) The consumer is responsible for implementing observability and telemetry. The application developer cannot implement observability features that function within the consumer's account.

3. You are responsible for deploying a Snowflake Native Application that processes sensitive financial dat a. Your team is concerned about data leakage and unauthorized access. Which of the following security measures should you implement to mitigate these risks and comply with Snowflake Marketplace best practices? (Select THREE)

A) Disable network policies on the application container to allow unrestricted access to external resources.
B) Implement Role-Based Access Control (RBAC) within the application, granting only the necessary privileges to each role.
C) Grant the APPLICATION ROLE access to all tables within the consumer's Snowflake account.
D) Implement Dynamic Data Masking on sensitive columns within the application's data container.
E) Use Snowflake Secrets to securely store and manage any API keys or credentials required by the application.

4. You are creating a Snowflake Native App using the Native Apps Framework. Your application needs to perform a task that must execute on a regular schedule (e.g., daily data refresh). Which Snowflake feature(s) can you leverage to achieve this, and what considerations are important when using them within the Native App context?

A) Snowflake Streams should be used to track data changes and trigger the refresh process. The Stream must be defined in the application package, and a separate task can be configured to consume the stream data.
B) You should implement an external scheduler (e.g., AWS Lambda, Azure Functions) that triggers a Snowflake Stored Procedure via the Snowflake API. The Stored Procedure should be owned by the APPLICATION role.
C) Snowflake Tasks can be used directly within the Native App, but you must ensure the task definition is part of the application package and the task is resumed upon installation in the consumer account. The task must use the APPLICATION role.
D) Snowflake Pipes are the preferred method for scheduled data ingestion within Native Apps, as they are designed for continuous data loading from external sources.
E) Use Snowflake Alerts with a cron schedule to trigger a stored procedure owned by the APPLICATION role. The procedure executes any scheduled task.

5. You are developing a Snowflake Native Application using Scala for a financial institution. The application processes sensitive transaction dat a. During consumer-side testing, the consumer reports intermittent 'java.lang.NullPointerException' errors. You suspect the issue lies within your UDE How can you effectively trace and debug this issue, considering data privacy requirements and without directly exposing sensitive consumer data in your logs?

A) Implement a custom error handling mechanism in Scala that catches 'NullPointerException', logs a generic error message with a unique error code to the event table, and then re-throws a more descriptive exception to the consumer. The consumer can then report the error code to the provider for further investigation. The provider can analyze the code, without actual consumer sensitive data.
B) Implement structured logging within the Scala UDF using SLF4J and Logback. Include contextual information (e.g., transaction IDs, timestamps) at various stages of the UDF execution. Use Snowflake's masking policies on the event table to protect sensitive data during logging. This is the best method as it's the more granular and effective
C) Utilize 'System.out.println' statements within the Scala UDF to print debug messages directly to the query result. The consumer can view these messages to identify the source of the error, with the provider having no visibility.
D) Rely solely on Snowflake's query history to identify failing queries. Analyze the input data and execution plan to infer the cause of the NullPointerException.
E) Use Snowflake's event table to capture all exceptions, filtering for the UDF name. Redact potentially sensitive fields in the logs after extraction using a Python script executed on the provider side.

Solutions: