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Google Associate Data Practitioner Exam - Topic 1 Question 24 Discussion

Your team wants to create a monthly report to analyze inventory data that is updated daily. You need to aggregate the inventory counts by using only the most recent month of data, and save the results to be used in a Looker Studio dashboard. What should you do?
A) Create a materialized view in BigQuery that uses the SUM( ) function and the DATE_SUB( ) function.
B) Create a saved query in the BigQuery console that uses the SUM( ) function and the DATE_SUB( ) function. Re-run the saved query every month, and save the results to a BigQuery table.
C) Create a BigQuery table that uses the SUM( ) function and the _PARTITIONDATE filter.
D) Create a BigQuery table that uses the SUM( ) function and the DATE_DIFF( ) function.

Google Associate Data Practitioner Exam - Topic 1 Question 24 Discussion

Actual exam question for Google's Associate Data Practitioner exam
Question #: 24
Topic #: 1
[All Associate Data Practitioner Questions]

Your team wants to create a monthly report to analyze inventory data that is updated daily. You need to aggregate the inventory counts by using only the most recent month of data, and save the results to be used in a Looker Studio dashboard. What should you do?

Show Suggested Answer Hide Answer
Suggested Answer: A

Creating a materialized view in BigQuery with the SUM() function and the DATE_SUB() function is the best approach. Materialized views allow you to pre-aggregate and cache query results, making them efficient for repeated access, such as monthly reporting. By using the DATE_SUB() function, you can filter the inventory data to include only the most recent month. This approach ensures that the aggregation is up-to-date with minimal latency and provides efficient integration with Looker Studio for dashboarding.


by Bethanie at May 07, 2026, 12:44 PM

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Alpha
4 days ago
B allows for flexibility. I like that approach.
upvoted 0 times
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Reynalda
9 days ago
I feel A is more reliable. Less manual work needed.
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Madonna
14 days ago
C is interesting. It could simplify data retrieval.
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Ilona
19 days ago
B seems practical. Monthly re-runs are manageable.
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Bette
24 days ago
I’m leaning towards A. It updates automatically, right?
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Mireya
30 days ago
Option C sounds good too. Partitioning helps with performance.
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Noemi
1 month ago
I prefer option B. Saved queries are easy to manage.
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Natalie
1 month ago
I think option A is the best. Materialized views are efficient.
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Aaron
2 months ago
Totally agree with C, it simplifies the aggregation process!
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Marla
2 months ago
Wait, can we really rely on the _PARTITIONDATE filter for accuracy?
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Alverta
2 months ago
C is the way to go! Partitioning makes it easier to manage data.
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Casie
2 months ago
I think B is better since it allows for more control over the query.
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Elouise
2 months ago
Option A sounds efficient with the materialized view!
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Alonso
2 months ago
Option D seems off to me; I don't think DATE_DIFF( ) would help with aggregating inventory counts like the other options.
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Heidy
4 months ago
I feel like using _PARTITIONDATE in option C could be beneficial for performance, but I can't recall if it fits the requirement for the most recent month.
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Alayna
4 months ago
I remember practicing with saved queries, so option B might be the right choice since it allows for re-running the query monthly.
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Hobert
4 months ago
I think option A sounds familiar, but I'm not entirely sure how materialized views work in this context.
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