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ARA-R01 Exam Dumps : SnowPro Advanced: Architect Recertification Exam

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SnowPro Advanced: Architect Recertification Exam Questions and Answers

Question 1

A company has a Snowflake account named ACCOUNTA in AWS us-east-1 region. The company stores its marketing data in a Snowflake database named MARKET_DB. One of the company’s business partners has an account named PARTNERB in Azure East US 2 region. For marketing purposes the company has agreed to share the database MARKET_DB with the partner account.

Which of the following steps MUST be performed for the account PARTNERB to consume data from the MARKET_DB database?

Options:

A.

Create a new account (called AZABC123) in Azure East US 2 region. From account ACCOUNTA create a share of database MARKET_DB, create a new database out of this share locally in AWS us-east-1 region, and replicate this new database to AZABC123 account. Then set up data sharing to the PARTNERB account.

B.

From account ACCOUNTA create a share of database MARKET_DB, and create a new database out of this share locally in AWS us-east-1 region. Then make this database the provider and share it with the PARTNERB account.

C.

Create a new account (called AZABC123) in Azure East US 2 region. From account ACCOUNTA replicate the database MARKET_DB to AZABC123 and from this account set up the data sharing to the PARTNERB account.

D.

Create a share of database MARKET_DB, and create a new database out of this share locally in AWS us-east-1 region. Then replicate this database to the partner’s account PARTNERB.

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Question 2

A user, analyst_user has been granted the analyst_role, and is deploying a SnowSQL script to run as a background service to extract data from Snowflake.

What steps should be taken to allow the IP addresses to be accessed? (Select TWO).

Options:

A.

ALTERROLEANALYST_ROLESETNETWORK_POLICY='ANALYST_POLICY';

B.

ALTERUSERANALYSTJJSERSETNETWORK_POLICY='ANALYST_POLICY';

C.

ALTERUSERANALYST_USERSETNETWORK_POLICY='10.1.1.20';

D.

USE ROLE SECURITYADMIN;

CREATE OR REPLACE NETWORK POLICY ANALYST_POLICY ALLOWED_IP_LIST = ('10.1.1.20');

E.

USE ROLE USERADMIN;

CREATE OR REPLACE NETWORK POLICY ANALYST_POLICY

ALLOWED_IP_LIST = ('10.1.1.20');

Question 3

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?

Options:

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 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.

D.

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.