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 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.
• B.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.
• C.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.
• D.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.

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A company is designing high availability and disaster recovery plans and needs to maximize redundancy and minimize recovery time objectives for their critical application processes. Cost is not a concern as long as the solution is the best available. The plan so far consists of the following steps:
1. Deployment of Snowflake accounts on two different cloud providers.
2. Selection of cloud provider regions that are geographically far apart.
3. The Snowflake deployment will replicate the databases and account data between both cloud provider accounts.
4. Implementation of Snowflake client redirect.
What is the MOST cost-effective way to provide the HIGHEST uptime and LEAST application disruption if there is a service event?

• A.Connect the applications using the <organization_name>-<connection_name> URL. Use the Business Critical Snowflake edition.
• B.Connect the applications using the <organization_name>-<connection_name> URL. Use the Virtual Private Snowflake (VPS) edition.
• C.Connect the applications using the <organization_name>-<accountLocator> URL. Use the Enterprise Snowflake edition.
• D.Connect the applications using the <organization_name>-<accountLocator> URL. Use the Business Critical Snowflake edition.

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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.OWNERSHIP on the named pipe, USAGE on the 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.USAGE on the named pipe, named stage, target database, and schema, and INSERT and SELECT on the target table

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An Architect runs the following SQL query:

How can this query be interpreted?

• A.FILEROWS is a stage. FILE_ROW_NUMBER is line number in file.
• B.FILEROWS is the table. FILE_ROW_NUMBER is the line number in the table.
• C.FILEROWS is a file. FILE_ROW_NUMBER is the file format location.
• D.FILERONS is the file format location. FILE_ROW_NUMBER is a stage.

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Which Snowflake data modeling approach is designed for BI queries?

• A.3 NF
• B.Star schema
• C.Data Vault
• D.Snowflake schema

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