ARA-R01 무료 덤프문제 온라인 액세스

There are two databases in an account, named fin_db and hr_db which contain payroll and employee data, respectively. Accountants and Analysts in the company require different permissions on the objects in these databases to perform their jobs. Accountants need read-write access to fin_db but only require read-only access to hr_db because the database is maintained by human resources personnel.
An Architect needs to create a read-only role for certain employees working in the human resources department.
Which permission sets must be granted to this role?

• A.MODIFY on database hr_db, USAGE on all schemas in database hr_db, USAGE on all tables in database hr_db
• B.USAGE on database hr_db, USAGE on all schemas in database hr_db, REFERENCES on all tables in database hr_db
• C.USAGE on database hr_db, SELECT on all schemas in database hr_db, SELECT on all tables in database hr_db
• D.USAGE on database hr_db, USAGE on all schemas in database hr_db, SELECT on all tables in database hr_db

When loading data into a table that captures the load time in a column with a default value of either CURRENT_TIME () or CURRENT_TIMESTAMP() what will occur?

• A.Any rows loaded using a specific COPY statement will have varying timestamps based on when the rows were created in the source.
• B.All rows loaded using a specific COPY statement will have varying timestamps based on when the rows were inserted.
• C.Any rows loaded using a specific COPY statement will have varying timestamps based on when the rows were read from the source.
• D.All rows loaded using a specific COPY statement will have the same timestamp value.

When using the Snowflake Connector for Kafka, what data formats are supported for the messages? (Choose two.)

• A.Parquet
• B.Avro
• C.JSON
• D.CSV
• E.XML

What is a characteristic of loading data into Snowflake using the Snowflake Connector for Kafka?

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

A media company needs a data pipeline that will ingest customer review data into a Snowflake table, and apply some transformations. The company also needs to use Amazon Comprehend to do sentiment analysis and make the de-identified final data set available publicly for advertising companies who use different cloud providers in different regions.
The data pipeline needs to run continuously and efficiently as new records arrive in the object storage leveraging event notifications. Also, the operational complexity, maintenance of the infrastructure, including platform upgrades and security, and the development effort should be minimal.
Which design will meet these requirements?

• A.Ingest the data using copy into and use streams and tasks to orchestrate transformations. Export the data into Amazon S3 to do model inference with Amazon Comprehend and ingest the data back into a Snowflake table. Then create a listing in the Snowflake Marketplace to make the data available to other companies.
• B.Ingest the data using Snowpipe and use streams and tasks to orchestrate transformations. Create an external function to do model inference with Amazon Comprehend and write the final records to a Snowflake table. Then create a listing in the Snowflake Marketplace to make the data available to other companies.
• C.Ingest the data using Snowpipe and use streams and tasks to orchestrate transformations. Export the data into Amazon S3 to do model inference with Amazon Comprehend and ingest the data back into a Snowflake table. Then create a listing in the Snowflake Marketplace to make the data available to other companies.
• D.Ingest the data into Snowflake using Amazon EMR and PySpark using the Snowflake Spark connector.
  Apply transformations using another Spark job. Develop a python program to do model inference by leveraging the Amazon Comprehend text analysis API. Then write the results to a Snowflake table and create a listing in the Snowflake Marketplace to make the data available to other companies.