- A
Update the fact table nightly to replace old customer keys with the current key
Why wrong: Updating facts destroys historical accuracy.
- B
Store the surrogate customer key from the dimension table in the fact table at transaction time
This ensures the fact always points to the correct version of the customer.
- C
Denormalize customer attributes into the fact table
Why wrong: Denormalization makes updates difficult and duplicates data.
- D
Use the natural customer ID in the fact table and join with the dimension using a BETWEEN condition on effective dates
Why wrong: Between joins can be inefficient and error-prone if dates are not precise.
Quick Answer
The correct approach is to store the surrogate customer key from the dimension table in the fact table at transaction time. This resolves the issue because with Type 2 slowly changing dimensions in BigQuery, each change to a customer’s attributes creates a new row with a unique surrogate key, preserving historical versions. By capturing that specific surrogate key in the fact table when the order occurs, the fact record is permanently linked to the exact customer attributes active at that moment, preventing incorrect historical aggregates when the dimension is updated nightly. On the Google Professional Cloud Database Engineer exam, this tests your understanding of SCD Type 2 implementation and the critical role of surrogate keys in maintaining referential integrity over time—a common trap is assuming a natural key or current key suffices for historical joins. Remember the memory tip: “Stamp the surrogate at transaction time to freeze the facts in time.”
PCDE Practice Question: Define data structures and implement SQL for Business Intelligence
This PCDE practice question tests your understanding of define data structures and implement sql for business intelligence. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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 BI team uses BigQuery to report on customer orders. The 'customers' dimension table is updated nightly with Type 2 Slowly Changing Dimensions (SCD). However, some reports show incorrect historical aggregates because the fact table references only the current customer key. Which approach resolves this issue?
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
Store the surrogate customer key from the dimension table in the fact table at transaction time
Option B is correct because with Type 2 SCD, each customer row has a unique surrogate key that represents a specific version of the customer's attributes over time. Storing that surrogate key in the fact table at transaction time ensures that historical facts are permanently linked to the correct customer attributes as they existed at the time of the order. This prevents incorrect aggregates when the dimension table is updated, as the fact table will always join to the precise version of the customer record that was active when the transaction occurred.
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.
- ✗
Update the fact table nightly to replace old customer keys with the current key
Why it's wrong here
Updating facts destroys historical accuracy.
- ✓
Store the surrogate customer key from the dimension table in the fact table at transaction time
Why this is correct
This ensures the fact always points to the correct version of the customer.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Denormalize customer attributes into the fact table
Why it's wrong here
Denormalization makes updates difficult and duplicates data.
- ✗
Use the natural customer ID in the fact table and join with the dimension using a BETWEEN condition on effective dates
Why it's wrong here
Between joins can be inefficient and error-prone if dates are not precise.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the misconception that updating the fact table with current keys (Option A) is acceptable for Type 2 SCD, when in reality it silently converts the design to Type 1 and destroys historical accuracy.
Detailed technical explanation
How to think about this question
In BigQuery, Type 2 SCD is commonly implemented by adding a surrogate key column (e.g., `customer_sk`) and effective date columns (`valid_from`, `valid_to`) to the dimension table. When a fact row is inserted at transaction time, the correct surrogate key is looked up using the transaction timestamp against the dimension's date range, ensuring point-in-time accuracy. A subtle behavior is that BigQuery's partitioning and clustering on the dimension's effective date columns can dramatically speed up these lookups, but the fact table must store the surrogate key at ingestion time to avoid expensive joins that scan the entire dimension history.
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 cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
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FAQ
Questions learners often ask
What does this PCDE question test?
Define data structures and implement SQL for Business Intelligence — This question tests Define data structures and implement SQL for Business Intelligence — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Store the surrogate customer key from the dimension table in the fact table at transaction time — Option B is correct because with Type 2 SCD, each customer row has a unique surrogate key that represents a specific version of the customer's attributes over time. Storing that surrogate key in the fact table at transaction time ensures that historical facts are permanently linked to the correct customer attributes as they existed at the time of the order. This prevents incorrect aggregates when the dimension table is updated, as the fact table will always join to the precise version of the customer record that was active when the transaction occurred.
What should I do if I get this PCDE 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.
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Last reviewed: Jun 30, 2026
This PCDE 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 PCDE exam.
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