hardMultiple Select
PDE Practice Question: A payment processing company needs to detect…
A payment processing company needs to detect fraudulent transactions in real time. The system must have sub-second latency for high-value transactions and use a machine learning model. Which two components should be part of the architecture? (Choose TWO.)
⚠ Common exam trap
Google Cloud often tests the distinction between storage services optimized for real-time access (Bigtable) versus batch/archive (Cloud Storage) and between stream processing (Dataflow) versus batch processing or short-lived compute (Cloud Functions).
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Bigtable to store user profiles and transaction history for fast lookups
Bigtable is a fully managed, scalable NoSQL database that provides consistent sub-10ms latency for high-throughput read/write operations, making it ideal for real-time lookups of user profiles and transaction history in fraud detection. Its ability to handle large volumes of data with low latency supports the sub-second requirement for high-value transactions.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Cloud Storage for transaction logs
Why it's wrong here
Cloud Storage is batch-oriented and does not support low-latency access needed for online fraud detection.
- ✓
Bigtable to store user profiles and transaction history for fast lookups
Why this is correct
Bigtable offers sub-millisecond latency for point lookups, essential for real-time fraud scoring.
- ✓
Dataflow for stream processing with sliding windows
Why this is correct
Dataflow can aggregate events in sliding windows and call a machine learning model for each window.
- ✗
Cloud SQL to store reference data
Why it's wrong here
Cloud SQL cannot handle the throughput and latency requirements for real-time fraud detection with high transaction volumes.
- ✗
Cloud Functions for long-running batch model training
Why it's wrong here
Cloud Functions has a timeout limit and is not suitable for training models; it is event-driven and short-lived.
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