Discuss Snowflake ARA-C01 Exam Topic 6 Question 50

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?

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 tables.

CCopy the data between providers from S3 to Azure Blob storage to collocate, then use Snowpipe for data ingestion.

DUse 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.

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.

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33 comments · newest first

Essie 10 months ago

A is definitely the way to go for minimizing costs.

Krissy 10 months ago

Surprised that D is even an option, seems like extra steps!

William 10 months ago

Option A seems like the best choice for low overhead.

Goldie 10 months ago

C sounds complicated, not sure it's worth the effort.

Dorthy 11 months ago

I disagree, B might be more efficient for frequent changes.

Melissa 11 months ago

I feel like option D could be a good choice since it involves replication, but I’m not sure how that impacts operational overhead compared to the others.

Eleni 11 months ago

I’m a bit confused about the egress costs. Would copying data to Azure Blob storage really minimize those costs?

Lynelle 11 months ago

I think option B sounds familiar; it might help with low latency since it keeps the data accessible without too much overhead.

Ryan 11 months ago

I remember we discussed external tables in class, but I'm not sure if using a materialized view is the best option for frequently changing data.

Ashley 12 months ago

I think I've got a good handle on this. Option C seems like the best approach, as it allows for efficient data ingestion using Snowpipe while keeping the data within the Azure ecosystem.

Adria 12 months ago

Option D looks promising, as it leverages the AWS Transfer Family to replicate the data between the S3 bucket and Azure Blob storage. This could help maintain low latency and minimize operational overhead.

Kayleigh 12 months ago

I'm a bit confused by the different cloud providers involved. I'll need to carefully review the options to determine the most efficient and cost-effective solution.

Darnell 1 year ago

Hmm, the key here is minimizing operational overhead while meeting the requirements. I'm leaning towards option C, as it seems to address the need for frequent data updates and low egress costs.

Enola 1 year ago

This question seems straightforward, but I want to make sure I fully understand the requirements before selecting an answer.

Roxane 1 year ago

You know, Option A with the materialized view might not be a bad idea. That could give us the frequent data access we need without too much overhead. Worth considering, for sure.

Alysa 1 year ago

↳ replying to Roxane

Yeah, I agree. It seems like a practical option to meet the requirements with minimal operational overhead.

Moon 1 year ago

↳ replying to Roxane

Option A with the materialized view sounds like a good solution. It could help with frequent data access.

Venita 1 year ago

Haha, Option D with the AWS Transfer Family? Sounds like a complicated workaround just to get the data where we need it. I'd rather keep it simple and go with Option B.

Lindsey 1 year ago

↳ replying to Venita

Let's go with Option B then, it's the least amount of operational overhead.

Ezekiel 1 year ago

↳ replying to Venita

Yeah, keeping it simple is usually the best way to go.

Laurel 1 year ago

↳ replying to Venita

I agree, Option B seems like a simpler approach to meet the requirements.

Aliza 1 year ago

↳ replying to Venita

Option D with AWS Transfer Family seems like a complex solution.

Barney 1 year ago

I'm not sure about Option C. Copying the data between providers seems like it could get messy and increase the operational overhead. We should try to minimize that as much as possible.

Ashleigh 1 year ago

↳ replying to Barney

B) Use an external table against the S3 bucket in AWS Singapore and copy the data into transient tables.

Avery 1 year ago

↳ replying to Barney

A) Use a materialized view on top of an external table against the S3 bucket in AWS Singapore.

Franchesca 1 year ago

But wouldn't using external tables against the S3 bucket in AWS Singapore be more cost-effective?

Sue 1 year ago

I prefer option D, replicating data between providers could be more reliable.

Anjelica 1 year ago

Option B looks like the way to go. Keeping the data in the external table and copying it into transient tables should provide the frequently changing data access and low latency we need.

Holley 1 year ago

↳ replying to Anjelica

Agreed. It seems like the most efficient way to handle the data analysis process.

Melita 1 year ago

↳ replying to Anjelica

That sounds like a good solution. It should meet all the requirements without too much operational overhead.

Charlene 1 year ago

↳ replying to Anjelica

B) Use an external table against the S3 bucket in AWS Singapore and copy the data into transient tables.

Elvis 1 year ago

I agree with Franchesca, using Snowpipe for data ingestion seems efficient.

Franchesca 1 year ago

I think option C sounds like a good solution.

Snowflake ARA-C01 Exam - Topic 6 Question 50 Discussion