Free Google Cloud-Digital-Leader Actual Exam Questions - Question 10 Discussion

I agree that D sounds off since data warehouses don’t usually turn structured into unstructured data. But A also seems unlikely because while some warehouses support dashboards, “natively visualizing both text and speech data in real time” isn’t their core strength. The question emphasizes why a cloud warehouse suits this scenario, so it’s really about ingesting and analyzing huge amounts of mixed data. Wouldn’t that make B the best fit? C feels unrelated since data security between environments isn’t the main problem here. Anyone else think the real focus is on scale and variety rather than v

B/D? Warehouses aren’t typically used to convert data types, so D feels off. The key is probably handling both data forms at scale, so B still clicks better from a capability angle.

Option B makes sense because a cloud data warehouse can handle large-scale data ingestion and analysis, especially for mixed structured and unstructured text and speech transcripts. It’s about managing volume and variety efficiently.

B, it’s about handling and analyzing varied data types efficiently at scale.

It’s B, cloud warehouses handle lots of data types fast, perfect here.

B since they need to analyze both text and speech data efficiently at scale.

I think A is off since real-time dashboards are usually separate services, not the core of a warehouse. B looks good because it covers both data types and scaling. So, B.

B imo, because cloud warehouses are built for handling tons of data types fast, not just visualizing or securing. Also, A and C don’t really address the core need of analyzing mixed data at scale.

Maybe B makes the most sense since cloud warehouses can handle huge volumes of mixed data types quickly. Options A and C don’t really fit the core need here, and D seems off because you usually transform unstructured to structured, not the other way.

B - Cloud warehouses handle both structured and unstructured data well, perfect for scaling.

It’s B, but I wonder if the question implies real-time analysis with low latency or just massive scale over time? Because some cloud warehouses are better at batch processing. Also, does the “speech data” mean raw audio files or just transcriptions? That might affect whether a data warehouse is the best tool or if a separate speech analytics service is needed.