ARA-C01 · Question #153
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…
The correct answer is B. Ingest the data using Snowpipe and use streams and tasks to orchestrate transformations. Create. Option B is the best design to meet the requirements because it uses Snowpipe to ingest the data continuously and efficiently as new records arrive in the object storage, leveraging event notifications. Snowpipe is a service that automates the loading of data from external…
Question
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
- AIngest the data using copy into and use streams and tasks to orchestrate transformations. Export
- BIngest the data using Snowpipe and use streams and tasks to orchestrate transformations. Create
- CIngest the data into Snowflake using Amazon EMR and PySpark using the Snowflake Spark
- DIngest the data using Snowpipe and use streams and tasks to orchestrate transformations. Export
How the community answered
(46 responses)- A22% (10)
- B65% (30)
- C4% (2)
- D9% (4)
Explanation
Option B is the best design to meet the requirements because it uses Snowpipe to ingest the data continuously and efficiently as new records arrive in the object storage, leveraging event notifications. Snowpipe is a service that automates the loading of data from external sources into Snowflake tables. It also uses streams and tasks to orchestrate transformations on the ingested data. Streams are objects that store the change history of a table, and tasks are objects that execute SQL statements on a schedule or when triggered by another task. Option B also uses an external function to do model inference with Amazon Comprehend and write the final records to a Snowflake table. An external function is a user-defined function that calls an external API, such as Amazon Comprehend, to perform computations that are not natively supported by Snowflake. Finally, option B uses the Snowflake Marketplace to make the de-identified final data set available publicly for advertising companies who use different cloud providers in different regions. The Snowflake Marketplace is a platform that enables data providers to list and share their data sets with data consumers, regardless of the cloud platform or region they use.
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