Q: 5
Cumulus Financial wants to be able to track the daily transaction volume of each of its customers in
real time and send out a notification as soon as it detects volume outside a customer's normal range.
What should a consultant do to accommodate this request?
Options
Discussion
Option C
Makes sense to go with C here. Streaming insight can watch real-time metrics and trigger actions right away, which fits the need for instant notifications on abnormal volume. I think that's the exact use case it's built for, but open to other views.
C . Streaming insight with a data action fits because it's set up for live pattern detection and instant alerts, just what the scenario is asking for. Practice exams and official docs both highlight this combo when you need true real-time notifications. If anyone's seen a Salesforce doc that says otherwise, let me know.
Wouldn't streaming insight (option C) be better than just a data transform for catching anomalies as they happen? I thought transforms just prep the data, but insights let you define those "out of range" triggers and hook them up to actions. Maybe I'm missing something, but don't think B or D would alert in real time by themselves.
Option C Streaming insights are built for this kind of real-time pattern detection, and pairing with a data action handles notifications immediately.
D imo. Streaming data transform with a data action sounded closer since transforms handle live pipeline changes and a data action could fire off alerts. Saw similar logic in some practice tests but not 100% sure, might want to check the Salesforce guide for real-time detection details. Do you agree or am I missing something?
C tbh, streaming insight handles the real-time monitoring, then data action fires off alerts. Data transform just preps the stream, doesn't actually do the anomaly detection or notifications. Pretty confident but shout if you see it differently.
Nah, I think C is right for this. Streaming insight plus data action is designed for real-time anomaly detection, while D looks similar but streaming transform is more about data prep than event logic. D's a common trap here!
Seen similar on practice exams, and it's all about real-time detection so C fits. Streaming insight + data action is what's recommended for instant anomaly triggers per official docs. If anyone's used something else lately let me know.
Its C, since streaming insight actually lets you analyze and detect outlier transaction volumes as they happen. The data action part connects directly to notifications. Pretty sure about this but interested if anyone has seen a real case where D was better.
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