- A
Use Datastream to stream changes from MySQL to BigQuery
Datastream handles schema changes automatically and provides low-latency streaming with minimal manual intervention.
- B
Use BigQuery Data Transfer Service for MySQL
Why wrong: BigQuery Data Transfer Service does not support MySQL as a source.
- C
Export MySQL data to CSV, upload to GCS, and use BigQuery load jobs
Why wrong: This approach requires manual handling of schema changes and daily exports, which is more operational overhead.
- D
Use Cloud SQL federated query from BigQuery
Why wrong: Federated queries are suitable for ad-hoc analysis but not for daily scheduled loads, and they may incur high costs for repeated queries.
Question 364 of 1,000
PDE Ingesting and Processing the Data Practice Question
This PDE practice question tests your understanding of ingesting and processing the data. Compare every option against the stated constraints before choosing — the best answer satisfies all requirements, not just the most obvious one. 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 company needs to load data from a MySQL database into BigQuery daily. The data volume is 10 GB per day and the schema changes occasionally. They want to minimize costs and operational overhead. What is the MOST appropriate approach?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"minimum / minimize"Why it matters: Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
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 Datastream to stream changes from MySQL to BigQuery
Datastream is the most appropriate approach because it provides a serverless, change data capture (CDC) solution that continuously replicates changes from MySQL to BigQuery with minimal latency. It handles schema evolution automatically, reducing operational overhead, and its pay-per-GB pricing model minimizes costs for the 10 GB daily volume. This eliminates the need for manual exports or batch loads while ensuring data freshness.
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.
- ✓
Use Datastream to stream changes from MySQL to BigQuery
Why this is correct
Datastream handles schema changes automatically and provides low-latency streaming with minimal manual intervention.
Clue confirmation
The clue word "minimum / minimize" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use BigQuery Data Transfer Service for MySQL
Why it's wrong here
BigQuery Data Transfer Service does not support MySQL as a source.
- ✗
Export MySQL data to CSV, upload to GCS, and use BigQuery load jobs
Why it's wrong here
This approach requires manual handling of schema changes and daily exports, which is more operational overhead.
- ✗
Use Cloud SQL federated query from BigQuery
Why it's wrong here
Federated queries are suitable for ad-hoc analysis but not for daily scheduled loads, and they may incur high costs for repeated queries.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Cisco often tests the misconception that BigQuery Data Transfer Service supports any database source, but it only supports specific SaaS and cloud storage sources, not direct MySQL connections.
Detailed technical explanation
How to think about this question
Datastream uses MySQL binary log replication to capture row-level changes (inserts, updates, deletes) in near real-time, then streams them into BigQuery via a staging area in Cloud Storage. It automatically detects schema changes (e.g., new columns) and applies them to the BigQuery table using BigQuery's schema auto-detection, avoiding table rebuilds. In a real-world scenario, if a column is added to the MySQL table, Datastream will append the new column to the BigQuery table without downtime, whereas batch CSV loads would require a schema update and reload of all data.
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 startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
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 |
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.
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Ingesting and Processing the Data — study guide chapter
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FAQ
Questions learners often ask
What does this PDE question test?
Ingesting and Processing the Data — This question tests Ingesting and Processing the Data — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use Datastream to stream changes from MySQL to BigQuery — Datastream is the most appropriate approach because it provides a serverless, change data capture (CDC) solution that continuously replicates changes from MySQL to BigQuery with minimal latency. It handles schema evolution automatically, reducing operational overhead, and its pay-per-GB pricing model minimizes costs for the 10 GB daily volume. This eliminates the need for manual exports or batch loads while ensuring data freshness.
What should I do if I get this PDE 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: "minimum / minimize". Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
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Last reviewed: Jul 4, 2026
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.
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