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Google Professional Data Engineer Exam - Topic 1 Question 38 Discussion

You are building a report-only data warehouse where the data is streamed into BigQuery via the streaming API Following Google's best practices, you have both a staging and a production table for the data How should you design your data loading to ensure that there is only one master dataset without affecting performance on either the ingestion or reporting pieces?
D) Have a staging table that moves the staged data over to the production table and deletes the contents of the staging table every thirty minutes
A) Have a staging table that is an append-only model, and then update the production table every three hours with the changes written to staging
B) Have a staging table that is an append-only model, and then update the production table every ninety minutes with the changes written to staging
C) Have a staging table that moves the staged data over to the production table and deletes the contents of the staging table every three hours

Google Professional Data Engineer Exam - Topic 1 Question 38 Discussion

Actual exam question for Google's Professional Data Engineer exam
Question #: 38
Topic #: 1
[All Professional Data Engineer Questions]

You are building a report-only data warehouse where the data is streamed into BigQuery via the streaming API Following Google's best practices, you have both a staging and a production table for the data How should you design your data loading to ensure that there is only one master dataset without affecting performance on either the ingestion or reporting pieces?

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Suggested Answer: D

by Mireya at May 10, 2022, 01:38 AM

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Charlena
10 months ago
Not sure if updating every three hours is fast enough for real-time needs.
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Rolf
10 months ago
I like the idea of keeping it append-only in staging, so A or B are good.
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Frankie
11 months ago
Surprised that no one mentioned the potential data loss with option C!
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Kate
11 months ago
I disagree, option D seems more efficient with the 30-minute updates.
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Dorothy
11 months ago
I think option B makes the most sense for performance.
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Andree
11 months ago
I recall that frequent updates can help maintain performance, but I wonder if thirty minutes is too aggressive. It seems like it could lead to more overhead.
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Elouise
11 months ago
I’m a bit confused about whether moving data to production and deleting the staging contents is the best approach. I thought we should keep staging intact for a while.
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Rima
11 months ago
I think we practiced a similar question where the frequency of updates was crucial. I feel like every ninety minutes might strike a good balance for performance.
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Ryan
11 months ago
I remember we discussed the importance of keeping the staging table append-only to avoid data loss, but I'm not sure about the timing for updating the production table.
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Andra
11 months ago
This is a tricky one. I'll need to think carefully about the cloud native trailmap and what it covers.
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Micaela
11 months ago
This seems straightforward - we need to give external researchers and internal staff access to collaborate, so I think creating a portal for the external researchers and giving the internal staff access to the main org is the way to go.
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Tijuana
11 months ago
I'm pretty sure it's a prefix of Splunk_TA_, but I'll double-check the Splunk documentation to be sure.
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Marilynn
11 months ago
I remember a practice question that focused on the authority of the officer. Is that required too?
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