DEA-C02 Exam Dumps | You are designing a data loading process for a high-volume streaming data source. The data arrives as

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Question 99/149

You are designing a data loading process for a high-volume streaming data source. The data arrives as Avro files in an AWS S3 bucket. You need to load this data into a Snowflake table with minimal latency and operational overhead. Which of the following combinations of Snowflake features and configurations would be MOST suitable for this scenario? (Select TWO)

A. Use the 'COPY INTO' command with a scheduled task that runs every 5 minutes to load new files from the S3 bucket.

B. Implement Snowpipe with auto-ingest configured to listen for S3 event notifications whenever a new Avro file is added to the bucket.

C. Use a Kafka connector to stream data directly from the Kafka topic to Snowflake.

D. Create a custom Spark application that reads Avro files from S3, transforms the data, and then writes it to Snowflake using the Snowflake Spark connector.

E. Configure an external table pointing to the S3 bucket and query the Avro files directly from Snowflake.

Correct Answer: B,C

Explanation: Options B and C offer the best combination of low latency and operational efficiency for streaming data. Snowpipe with auto-ingest provides near real-time loading triggered by S3 events. A Kafka connector provides a direct data stream to Snowflake. Option A introduces latency due to the scheduled task interval and doesn't scale well for high-volume streams. Option D adds operational overhead with Spark application management. Option E is suitable for ad-hoc querying but not ideal for continuous data loading.

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