Discuss Google Associate Data Practitioner Exam Topic 1 Question 24

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?

ACreate a materialized view in BigQuery that uses the SUM( ) function and the DATE_SUB( ) function.

BCreate 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.

CCreate a BigQuery table that uses the SUM( ) function and the _PARTITIONDATE filter.

DCreate a BigQuery table that uses the SUM( ) function and the DATE_DIFF( ) function.

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.

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26 comments · newest first

Laila 2 days ago

D seems complicated with DATE_DIFF.

Brittney 8 days ago

C sounds good too. Partitions help.

Juliann 13 days ago

B needs manual re-running though.

Cyndy 18 days ago

I prefer B. Easier to manage.

Bette 23 days ago

Materialized views are efficient for this.

Brittney 28 days ago

Why A?

Bette 1 month ago

I think option A is the best.

Vashti 1 month ago

D doesn’t seem as efficient. I’d avoid it.

Pete 1 month ago

C could save time with large datasets.

Alpha 2 months ago

B allows for flexibility. I like that approach.

Reynalda 2 months ago

I feel A is more reliable. Less manual work needed.

Madonna 2 months ago

C is interesting. It could simplify data retrieval.

Ilona 2 months ago

B seems practical. Monthly re-runs are manageable.

Bette 2 months ago

I’m leaning towards A. It updates automatically, right?

Mireya 2 months ago

Option C sounds good too. Partitioning helps with performance.

Noemi 3 months ago

I prefer option B. Saved queries are easy to manage.

Natalie 3 months ago

I think option A is the best. Materialized views are efficient.

Aaron 3 months ago

Totally agree with C, it simplifies the aggregation process!

Marla 3 months ago

Wait, can we really rely on the _PARTITIONDATE filter for accuracy?

Alverta 3 months ago

C is the way to go! Partitioning makes it easier to manage data.

Casie 4 months ago

I think B is better since it allows for more control over the query.

Elouise 4 months ago

Option A sounds efficient with the materialized view!

Alonso 4 months ago

Option D seems off to me; I don't think DATE_DIFF( ) would help with aggregating inventory counts like the other options.

Heidy 5 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.

Alayna 6 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.

Hobert 6 months ago

I think option A sounds familiar, but I'm not entirely sure how materialized views work in this context.

Google Associate Data Practitioner Exam - Topic 1 Question 24 Discussion