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ARA-C01 · Question #161

A company is using Snowflake in Azure in the Netherlands. The company analyst team also has data in JSON format that is stored in an Amazon S3 bucket in the AWS Singapore region that the team wants to

The correct answer is B. Use an external table against the S3 bucket in AWS Singapore and copy the data into transient. An external table against the S3 bucket allows Snowflake (in Azure Netherlands) to query the JSON data in-place without fully migrating it, minimizing egress costs. Copying the result data into transient tables (which lack Fail-safe and have lower storage costs) caches frequently

Architectural Principles and Best Practices

Question

A company is using Snowflake in Azure in the Netherlands. The company analyst team also has data in JSON format that is stored in an Amazon S3 bucket in the AWS Singapore region that the team wants to analyze. The Architect has been given the following requirements: 1. Provide access to frequently changing data 2. Keep egress costs to a minimum 3. Maintain low latency How can these requirements be met with the LEAST amount of operational overhead?

Options

  • AUse a materialized view on top of an external table against the S3 bucket in AWS Singapore.
  • BUse an external table against the S3 bucket in AWS Singapore and copy the data into transient
  • CCopy the data between providers from S3 to Azure Blob storage to collocate, then use Snowpipe
  • DUse AWS Transfer Family to replicate data between the S3 bucket in AWS Singapore and an

How the community answered

(33 responses)
  • A
    24% (8)
  • B
    58% (19)
  • C
    6% (2)
  • D
    12% (4)

Explanation

An external table against the S3 bucket allows Snowflake (in Azure Netherlands) to query the JSON data in-place without fully migrating it, minimizing egress costs. Copying the result data into transient tables (which lack Fail-safe and have lower storage costs) caches frequently-used query results, reducing repeated cross-cloud latency for dashboards. When the source data changes, the external table always reflects the latest files. Option A (materialized view on external table) requires manual or scheduled refresh and lags on frequently changing data. Option C copies all data from S3 to Azure Blob Storage, incurring full cross-provider egress costs. Option D (AWS Transfer Family) adds significant operational overhead and replication complexity.

Topics

#Data Ingestion#External Tables#Cost Optimization#Cross-Cloud Data Management

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