PDE Ingesting and Processing the Data Practice Question
A healthcare company needs to ingest HL7 messages from an on-premises system into Google Cloud. The messages arrive continuously and must be processed in near-real-time, with transformations applied before loading into BigQuery. The company wants to use a fully managed service for message ingestion and a serverless data processing service. They also need to ensure that the pipeline can handle bursts of traffic and that the data is encrypted at rest. Which TWO Google Cloud services should they use? (Choose two.)
⚠ Common exam trap
The trap here is selecting Dataproc or Data Fusion because they are data processing services, but they are not fully serverless and may require cluster management, which contradicts the requirement.
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
✓
Cloud Dataflow
Pub/Sub provides scalable, managed ingestion of HL7 messages with encryption at rest, and Dataflow offers serverless stream processing with autoscaling and exactly-once semantics. Together, they form a fully managed pipeline that can handle bursts and transform data before loading into BigQuery. Other services are either not serverless or not designed for real-time processing.
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 Data Fusion
Why it's wrong here
Cloud Data Fusion is a fully managed data integration service, but it is not serverless in the same sense as Dataflow; it requires provisioning an instance. It is more suited for ETL with a graphical interface and may not provide the low-latency, code-based transformations needed for HL7 processing. It also may not autoscale as seamlessly.
- ✓
Cloud Dataflow
Why this is correct
Dataflow is a fully managed, serverless service for stream and batch processing. It can read from Pub/Sub, apply transformations to HL7 messages, and write to BigQuery. It autoscales to handle traffic bursts and integrates with Cloud KMS for encryption. Dataflow provides exactly-once processing when needed and is ideal for near-real-time transformations.
- ✗
Cloud Dataproc
Why it's wrong here
Dataproc is a managed Spark and Hadoop service, but it is not serverless; it requires provisioning and managing clusters. While it can process streaming data, it is not the best fit for a fully managed, serverless requirement. It also does not provide the same level of autoscaling and ease of use as Dataflow for this scenario.
- ✓
Cloud Pub/Sub
Why this is correct
Pub/Sub is a fully managed, scalable messaging service that can ingest HL7 messages from on-premises systems via a pull subscription or push endpoint. It automatically scales to handle bursts and provides at-least-once delivery. It also encrypts data at rest by default, meeting the security requirement. Pub/Sub acts as the ingestion buffer for the pipeline.
- ✗
Cloud Composer
Why it's wrong here
Cloud Composer is a managed Apache Airflow service for workflow orchestration, not for data processing or message ingestion. It is used to schedule and monitor batch jobs, not to process streaming data in near-real-time. It would not handle the continuous flow of HL7 messages or provide the necessary transformations.
Quick reference
Cloud Service Model Comparison
| Model | You Manage | Provider Manages | Examples |
|---|---|---|---|
| IaaS | OS, runtime, apps, data | Hardware, hypervisor, networking | EC2, Azure VMs, GCP Compute Engine |
| PaaS | Apps and data | OS, runtime, middleware, hardware | Elastic Beanstalk, Azure App Service |
| SaaS | Data and settings only | Everything else | Microsoft 365, Salesforce, Workday |
| FaaS / Serverless | Function code only | Infra, scaling, runtime | Lambda, Azure Functions, Cloud Run |
| CaaS | Containers and apps | Kubernetes, OS, hardware | EKS, AKS, GKE |
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Google Cloud exam blueprint
This PDE practice question is part of Courseiva's free Google Cloud certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the PDE exam.