- A
Set up a Dataflow pipeline to continuously copy Cloud SQL changes to BigQuery
Why wrong: Dataflow adds complexity and cost for continuous replication; if analytics are not real-time, federated queries are simpler and cheaper.
- B
Use BigQuery federated queries to query Cloud SQL and GCS directly
BigQuery federated queries allow querying external data sources (Cloud SQL, GCS) without data movement, minimising cost and latency for analytics.
- C
Export the Cloud SQL data to CSV files in GCS and load them into BigQuery nightly
Why wrong: Manual export is not cost-effective or performant for real-time analytics; it also involves extra steps and potential delays.
- D
Replicate the Cloud SQL data to Cloud Bigtable and query it from there
Why wrong: Bigtable is not suitable for complex joins and analytical queries; it is designed for key-value lookups.
PCD Practice Question: Manage a Solution that Can Span Multiple Database Systems
This PCD practice question tests your understanding of manage a solution that can span multiple database systems. 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.
An e-commerce platform uses Cloud SQL for MySQL for transactional data and wants to run complex analytical queries on that data without affecting production performance. The analytics queries often join with data from Google Cloud Storage. What is the MOST cost-effective and performant approach?
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 BigQuery federated queries to query Cloud SQL and GCS directly
Option B is correct because BigQuery federated queries allow you to query Cloud SQL (MySQL) and Google Cloud Storage (GCS) directly using BigQuery's SQL engine, without moving data. This approach is cost-effective (no storage costs for duplicated data) and performant (BigQuery handles complex analytical joins efficiently), while avoiding any impact on the Cloud SQL production instance since queries are executed externally.
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.
- ✗
Set up a Dataflow pipeline to continuously copy Cloud SQL changes to BigQuery
Why it's wrong here
Dataflow adds complexity and cost for continuous replication; if analytics are not real-time, federated queries are simpler and cheaper.
- ✓
Use BigQuery federated queries to query Cloud SQL and GCS directly
Why this is correct
BigQuery federated queries allow querying external data sources (Cloud SQL, GCS) without data movement, minimising cost and latency for analytics.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Export the Cloud SQL data to CSV files in GCS and load them into BigQuery nightly
Why it's wrong here
Manual export is not cost-effective or performant for real-time analytics; it also involves extra steps and potential delays.
- ✗
Replicate the Cloud SQL data to Cloud Bigtable and query it from there
Why it's wrong here
Bigtable is not suitable for complex joins and analytical queries; it is designed for key-value lookups.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Cisco often tests the misconception that moving data to a separate analytics store (like BigQuery or Bigtable) is always necessary for performance, when in fact federated queries can avoid data duplication and reduce costs while still providing good performance for complex analytical joins.
Detailed technical explanation
How to think about this question
BigQuery federated queries use the BigQuery Storage API to read data from Cloud SQL via a JDBC connection, allowing BigQuery to push down filtering and aggregation to the source database where possible, minimizing data transfer. When joining with GCS data, BigQuery can read Parquet, Avro, or CSV files directly from external tables, leveraging columnar storage and predicate pushdown for performance. A real-world scenario is an e-commerce platform running daily sales reports that join recent transactions (in Cloud SQL) with historical product metadata (in GCS) without needing to maintain a separate data warehouse.
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.
What to study next
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this PCD question test?
Manage a Solution that Can Span Multiple Database Systems — This question tests Manage a Solution that Can Span Multiple Database Systems — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use BigQuery federated queries to query Cloud SQL and GCS directly — Option B is correct because BigQuery federated queries allow you to query Cloud SQL (MySQL) and Google Cloud Storage (GCS) directly using BigQuery's SQL engine, without moving data. This approach is cost-effective (no storage costs for duplicated data) and performant (BigQuery handles complex analytical joins efficiently), while avoiding any impact on the Cloud SQL production instance since queries are executed externally.
What should I do if I get this PCD question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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 PCD 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 PCD exam.
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