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Snowflake ARA-R01 Exam - Topic 1 Question 38 Discussion

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 data2. Keep egress costs to a minimum3. Maintain low latencyHow can these requirements be met with the LEAST amount of operational overhead?
B) Use an external table against the S3 bucket in AWS Singapore and copy the data into transient tables.
A) Use a materialized view on top of an external table against the S3 bucket in AWS Singapore.
C) Copy the data between providers from S3 to Azure Blob storage to collocate, then use Snowpipe for data ingestion.
D) Use AWS Transfer Family to replicate data between the S3 bucket in AWS Singapore and an Azure Netherlands Blob storage, then use an external table against the Blob storage.

Snowflake ARA-R01 Exam - Topic 1 Question 38 Discussion

Actual exam question for Snowflake's ARA-R01 exam
Question #: 38
Topic #: 1
[All ARA-R01 Questions]

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?

Show Suggested Answer Hide Answer
Suggested Answer: B

:Option A is the best design to meet the requirements because it uses a materialized view on top of an external table against the S3 bucket in AWS Singapore.A materialized view is a database object that contains the results of a query and can be refreshed periodically to reflect changes in the underlying data1.An external table is a table that references data files stored in a cloud storage service, such as Amazon S32. By using a materialized view on top of an external table, the company can provide access to frequently changing data, keep egress costs to a minimum, and maintain low latency. This is because the materialized view will cache the query results in Snowflake, reducing the need to access the external data files and incur network charges. The materialized view will also improve the query performance by avoiding scanning the external data files every time.The materialized view can be refreshed on a schedule or on demand to capture the changes in the external data files1.

Option B is not the best design because it uses an external table against the S3 bucket in AWS Singapore and copies the data into transient tables.A transient table is a table that is not subject to the Time Travel and Fail-safe features of Snowflake, and is automatically purged after a period of time3. By using an external table and copying the data into transient tables, the company will incur more egress costs and operational overhead than using a materialized view. This is because the external table will access the external data files every time a query is executed, and the copy operation will also transfer data from S3 to Snowflake. The transient tables will also consume more storage space in Snowflake and require manual maintenance to ensure they are up to date.

Option C is not the best design because it copies the data between providers from S3 to Azure Blob storage to collocate, then uses Snowpipe for data ingestion.Snowpipe is a service that automates the loading of data from external sources into Snowflake tables4. By copying the data between providers, the company will incur high egress costs and latency, as well as operational complexity and maintenance of the infrastructure. Snowpipe will also add another layer of processing and storage in Snowflake, which may not be necessary if the external data files are already in a queryable format.

Option D is not the best design because it uses AWS Transfer Family to replicate data between the S3 bucket in AWS Singapore and an Azure Netherlands Blob storage, then uses an external table against the Blob storage.AWS Transfer Family is a service that enables secure and seamless transfer of files over SFTP, FTPS, and FTP to and from Amazon S3 or Amazon EFS5. By using AWS Transfer Family, the company will incur high egress costs and latency, as well as operational complexity and maintenance of the infrastructure. The external table will also access the external data files every time a query is executed, which may affect the query performance.


by Muriel at Nov 25, 2025, 09:51 PM

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Ettie
3 months ago
True, but it adds complexity. Less overhead is key here.
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Blossom
4 months ago
Option D is interesting. Replication could simplify access.
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Maryann
4 months ago
I prefer option C. Collocating data reduces latency.
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Lindsey
4 months ago
Option B seems safer. External tables are easier to manage.
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Delisa
5 months ago
Wait, can you really use AWS Transfer Family like that? Sounds sketchy!
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Tayna
5 months ago
D? Really? That seems overly complicated for low latency.
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Robt
5 months ago
C seems like too much hassle with data transfer.
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Gilberto
5 months ago
I think B is better for keeping egress costs low.
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Elmira
5 months ago
Option A sounds efficient for frequently changing data.
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Ernie
5 months ago
Option D looks interesting, but I'm not sure about the latency with the data replication.
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Britt
6 months ago
Haha, I bet the architect is wishing they had a crystal ball to see all the options!
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Ashleigh
6 months ago
Hmm, I'm not sure about that. Copying the data between providers might add some unnecessary overhead.
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Sherly
6 months ago
Option B seems like the most straightforward approach to meet the requirements.
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Agustin
6 months ago
I think option B could work, but I'm not entirely sure if copying data into transient tables would really help with latency.
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Glenn
6 months ago
I think I'm leaning towards option D. Replicating the data between S3 and Azure Blob storage and then using an external table could be a good way to meet the requirements while minimizing overhead.
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Gianna
7 months ago
Okay, let's see. Frequent data changes, low egress costs, and low latency - that sounds like option C might be the way to go. Copying to Azure Blob and using Snowpipe could work well.
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Juan
7 months ago
I remember we discussed the importance of minimizing egress costs, so option A might not be the best choice since materialized views can incur additional costs.
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Lashawn
7 months ago
But won't that increase egress costs?
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Ettie
7 months ago
I think option A is the best. Materialized views are efficient.
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Shonda
7 months ago
I feel like option C is a bit complicated with the data transfer between providers, but it might be the best for low latency.
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Janine
8 months ago
I recall a practice question where we used AWS Transfer Family, so option D sounds familiar, but I'm not sure if it really meets the low latency requirement.
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Lakeesha
8 months ago
Hmm, I'm a bit confused by the different cloud providers involved. I'll need to make sure I understand how to work with data across AWS and Azure.
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Willodean
8 months ago
This looks like a tricky one! I'll need to carefully consider the requirements and the options to figure out the best approach.
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Mohammad
3 months ago
I’m leaning towards option B for a balance of simplicity and access.
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Domitila
3 months ago
True, but it sounds like more overhead.
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Kenneth
3 months ago
But what about egress costs? Option D could help with that.
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Chantell
3 months ago
I think option A might be the best for low latency.
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Della
3 months ago
This is definitely a challenging scenario!
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