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Snowflake ARA-C01 Exam is intended for experienced architects who have a deep understanding of Snowflake's cloud data platform and its capabilities. ARA-C01 exam tests the candidate's ability to design and implement complex data warehousing solutions, including data modeling, data integration, data transformation, and data analysis.

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Snowflake ARA-C01 exam is a performance-based exam that tests the candidate’s ability to solve real-world problems using Snowflake’s cloud data platform. ARA-C01 exam consists of a series of scenarios that require the candidate to design, implement, and optimize Snowflake solutions based on specific business requirements. ARA-C01 Exam is conducted online and can be taken from anywhere in the world.

Snowflake SnowPro Advanced Architect Certification Sample Questions (Q49-Q54):

NEW QUESTION # 49
A Data Engineer is designing a near real-time ingestion pipeline for a retail company to ingest event logs into Snowflake to derive insights. A Snowflake Architect is asked to define security best practices to configure access control privileges for the data load for auto-ingest to Snowpipe.
What are the MINIMUM object privileges required for the Snowpipe user to execute Snowpipe?

A. USAGE on the named pipe, named stage, target database, and schema, and INSERT and SELECT on the target table
B. OWNERSHIP on the named pipe, USAGE and READ on the named stage, USAGE on the target database and schema, and INSERT end SELECT on the target table
C. CREATE on the named pipe, USAGE and READ on the named stage, USAGE on the target database and schema, and INSERT end SELECT on the target table
D. OWNERSHIP on the named pipe, USAGE on the named stage, target database, and schema, and INSERT and SELECT on the target table

Answer: B

Explanation:
Explanation
According to the SnowPro Advanced: Architect documents and learning resources, the minimum object privileges required for the Snowpipe user to execute Snowpipe are:
* OWNERSHIP on the named pipe. This privilege allows the Snowpipe user to create, modify, and drop the pipe object that defines the COPY statement for loading data from the stage to the table1.
* USAGE and READ on the named stage. These privileges allow the Snowpipe user to access and read the data files from the stage that are loaded by Snowpipe2.
* USAGE on the target database and schema. These privileges allow the Snowpipe user to access the database and schema that contain the target table3.
* INSERT and SELECT on the target table. These privileges allow the Snowpipe user to insert data into the table and select data from the table4.
The other options are incorrect because they do not specify the minimum object privileges required for the Snowpipe user to execute Snowpipe. Option A is incorrect because it does not include the READ privilege on the named stage, which is required for the Snowpipe user to read the data files from the stage. Option C is incorrect because it does not include the OWNERSHIP privilege on the named pipe, which is required for the Snowpipe user to create, modify, and drop the pipe object. Option D is incorrect because it does not include the OWNERSHIP privilege on the named pipe or the READ privilege on the named stage, which are both required for the Snowpipe user to execute Snowpipe. References: CREATE PIPE | Snowflake Documentation, CREATE STAGE | Snowflake Documentation, CREATE DATABASE | Snowflake Documentation, CREATE TABLE | Snowflake Documentation

NEW QUESTION # 50
The diagram shows the process flow for Snowpipe auto-ingest with Amazon Simple Notification Service (SNS) with the following steps:
Step 1: Data files are loaded in a stage.
Step 2: An Amazon S3 event notification, published by SNS, informs Snowpipe - by way of Amazon Simple Queue Service (SQS) - that files are ready to load. Snowpipe copies the files into a queue.
Step 3: A Snowflake-provided virtual warehouse loads data from the queued files into the target table based on parameters defined in the specified pipe.

If an AWS Administrator accidentally deletes the SQS subscription to the SNS topic in Step 2, what will happen to the pipe that references the topic to receive event messages from Amazon S3?

A. The pipe will no longer be able to receive the messages. To restore the system immediately, the user needs to manually create a new SNS topic with a different name and then recreate the pipe by specifying the new SNS topic name in the pipe definition.
B. The pipe will continue to receive the messages as Snowflake will automatically restore the subscription to the same SNS topic and will recreate the pipe by specifying the same SNS topic name in the pipe definition.
C. The pipe will continue to receive the messages as Snowflake will automatically restore the subscription by creating a new SNS topic. Snowflake will then recreate the pipe by specifying the new SNS topic name in the pipe definition.
D. The pipe will no longer be able to receive the messages and the user must wait for 24 hours from the time when the SNS topic subscription was deleted. Pipe recreation is not required as the pipe will reuse the same subscription to the existing SNS topic after 24 hours.

Answer: A

NEW QUESTION # 51
Which semi structured data function interprets an input string as a JSON document, producing a VARIANT value.

A. PARSE_XML
B. PARSE_JSON
C. STRIP_JSON

Answer: B

NEW QUESTION # 52
Loading data using snowpipe REST API is supported for external stage only

A. TRUE
B. FALSE

Answer: B

NEW QUESTION # 53
What is a characteristic of loading data into Snowflake using the Snowflake Connector for Kafka?

A. Loads using the Connector will have lower latency than Snowpipe and will ingest data in real time.
B. The Connector only works in Snowflake regions that use AWS infrastructure.
C. The Connector works with all file formats, including text, JSON, Avro, Ore, Parquet, and XML.
D. The Connector creates and manages its own stage, file format, and pipe objects.

Answer: D

Explanation:
According to the SnowPro Advanced: Architect documents and learning resources, a characteristic of loading data into Snowflake using the Snowflake Connector for Kafka is that the Connector creates and manages its own stage, file format, and pipe objects. The stage is an internal stage that is used to store the data files from the Kafka topics. The file format is a JSON or Avro file format that is used to parse the data files. The pipe is a Snowpipe object that is used to load the data files into the Snowflake table. The Connector automatically creates and configures these objects based on the Kafka configuration properties, and handles the cleanup and maintenance of these objects1.
The other options are incorrect because they are not characteristics of loading data into Snowflake using the Snowflake Connector for Kafka. Option A is incorrect because the Connector works in Snowflake regions that use any cloud infrastructure, not just AWS. The Connector supports AWS, Azure, and Google Cloud platforms, and can load data across different regions and cloud platforms using data replication2. Option B is incorrect because the Connector does not work with all file formats, only JSON and Avro. The Connector expects the data in the Kafka topics to be in JSON or Avro format, and parses the data accordingly. Other file formats, such as text, ORC, Parquet, or XML, are not supported by the Connector3. Option D is incorrect because loads using the Connector do not have lower latency than Snowpipe, and do not ingest data in real time. The Connector uses Snowpipe to load data into Snowflake, and inherits the same latency and performance characteristics of Snowpipe. The Connector does not provide real-time ingestion, but near real-time ingestion, depending on the frequency and size of the data files4. Reference: Installing and Configuring the Kafka Connector | Snowflake Documentation, Sharing Data Across Regions and Cloud Platforms | Snowflake Documentation, Overview of the Kafka Connector | Snowflake Documentation, Using Snowflake Connector for Kafka With Snowpipe Streaming | Snowflake Documentation

NEW QUESTION # 54
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