Question 209 of 507
Why cloud technology is transforming businesshardMultiple ChoiceObjective-mapped

Cloud Digital Leader Why cloud technology is transforming business Practice Question

This GCDL practice question tests your understanding of why cloud technology is transforming business. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.

A multinational manufacturing company operates thousands of IoT sensors on factory equipment. These sensors generate over 50 TB of telemetry data daily. The company wants to implement predictive maintenance to reduce unplanned downtime. Their current on-premises infrastructure is maxed out, and they have a small IT team with limited data engineering expertise. They are evaluating cloud vs. on-premises options. The data is highly sensitive and must be encrypted at rest and in transit. Additionally, they need to run machine learning models near real-time and store historical data for trend analysis. The CTO is concerned about vendor lock-in, data sovereignty, and the ability to scale globally as they open new factories. Which course of action best addresses these requirements using Google Cloud?

Clue words in this question

Noticing these words before you look at the options changes how you read each choice.

  • Clue: "best"

    Why it matters: Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.

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

Use Cloud IoT Core to ingest sensor data, Cloud Pub/Sub for streaming, Cloud Dataflow for processing, and AI Platform for predictive models, all in the desired region.

Option C is correct because it leverages Google Cloud's fully managed services—Cloud IoT Core for ingestion, Pub/Sub for buffering, Dataflow for stream processing, and AI Platform for ML—to meet near-real-time predictive maintenance needs without requiring deep data engineering expertise. This architecture encrypts data at rest (Cloud Storage/AI Platform) and in transit (TLS), avoids vendor lock-in via open APIs, supports data sovereignty by deploying in a specific region, and scales globally as new factories are added.

Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Deploy Kubernetes on-premises to orchestrate microservices, and use Cloud Storage for backup only.

    Why it's wrong here

    Does not solve capacity constraints and still requires managing on-premises infrastructure.

  • Build a new on-premises data center with dedicated GPU servers for ML training, and hire additional data engineers.

    Why it's wrong here

    On-premises requires significant capital and staff, which the company lacks, and does not provide elasticity.

  • Use Cloud IoT Core to ingest sensor data, Cloud Pub/Sub for streaming, Cloud Dataflow for processing, and AI Platform for predictive models, all in the desired region.

    Why this is correct

    This fully managed solution scales, meets security/compliance, and reduces operational burden.

    Clue confirmation

    The clue word "best" in the question point toward this answer.

    Related concept

    Read the scenario before looking for a memorised answer.

  • Store all sensor data in Cloud Storage and run ad-hoc queries using BigQuery without any streaming pipeline.

    Why it's wrong here

    Lacks real-time processing and ML capabilities; BigQuery is not designed for streaming ML inference.

Common exam traps

Common exam trap: answer the scenario, not the keyword

Google Cloud often tests the misconception that batch processing (e.g., BigQuery on stored data) can substitute for a streaming pipeline in near-real-time scenarios, leading candidates to overlook the need for continuous ingestion and processing with services like Pub/Sub and Dataflow.

Detailed technical explanation

How to think about this question

Cloud IoT Core uses MQTT or HTTP protocols for device ingestion, automatically scaling to millions of devices, while Pub/Sub provides at-least-once delivery with low latency (typically under 100ms). Dataflow's autoscaling, based on Apache Beam, processes unbounded streams using exactly-once semantics, and AI Platform can deploy models as REST endpoints with automatic scaling, enabling sub-second predictions. This architecture also supports data residency by allowing all resources to be pinned to a specific Google Cloud region, satisfying data sovereignty requirements.

KKey Concepts to Remember

  • Read the scenario before looking for a memorised answer.
  • Find the constraint that changes the correct option.
  • Eliminate answers that are true in general but not in this case.

TExam Day Tips

  • Watch for words such as best, first, most likely and least administrative effort.
  • Review why wrong options are wrong, not only why the correct option is correct.

Key takeaway

Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.

Real-world example

How this comes up in practice

A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.

What to study next

Got this wrong? Here's your next step.

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

Related practice questions

Related GCDL practice-question pages

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FAQ

Questions learners often ask

What does this GCDL question test?

Why cloud technology is transforming business — This question tests Why cloud technology is transforming business — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: Use Cloud IoT Core to ingest sensor data, Cloud Pub/Sub for streaming, Cloud Dataflow for processing, and AI Platform for predictive models, all in the desired region. — Option C is correct because it leverages Google Cloud's fully managed services—Cloud IoT Core for ingestion, Pub/Sub for buffering, Dataflow for stream processing, and AI Platform for ML—to meet near-real-time predictive maintenance needs without requiring deep data engineering expertise. This architecture encrypts data at rest (Cloud Storage/AI Platform) and in transit (TLS), avoids vendor lock-in via open APIs, supports data sovereignty by deploying in a specific region, and scales globally as new factories are added.

What should I do if I get this GCDL question wrong?

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

Are there clue words in this question I should notice?

Yes — watch for: "best". Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

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Last reviewed: Jun 30, 2026

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This GCDL 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 GCDL exam.