- A
ARRAY
Why wrong: ARRAY is for repeated fields, not for varying structures.
- B
STRING
Why wrong: STRING can store raw text but lacks schema awareness and query capabilities for nested fields.
- C
FLOAT64
Why wrong: FLOAT64 is for numeric values, not complex structures.
- D
JSON
JSON type allows storing and querying semistructured data with nested fields.
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. 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 company needs to store raw event logs for future BI analysis. The logs are semistructured with varying fields. Which BigQuery data type should they use to store the event payload?
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
JSON
Option D is correct because BigQuery's JSON data type is designed to store semistructured data with varying fields, such as raw event logs. It allows schema flexibility, efficient querying of nested fields using JSON functions like `JSON_EXTRACT`, and avoids the need to predefine a rigid schema, which is ideal for BI analysis of event payloads.
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.
- ✗
ARRAY
Why it's wrong here
ARRAY is for repeated fields, not for varying structures.
- ✗
STRING
Why it's wrong here
STRING can store raw text but lacks schema awareness and query capabilities for nested fields.
- ✗
FLOAT64
Why it's wrong here
FLOAT64 is for numeric values, not complex structures.
- ✓
JSON
Why this is correct
JSON type allows storing and querying semistructured data with nested fields.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the misconception that STRING is sufficient for semistructured data, but the trap is that STRING lacks native querying capabilities and incurs higher costs for parsing, whereas JSON provides built-in functions and better performance for BI workloads.
Detailed technical explanation
How to think about this question
BigQuery's JSON data type internally stores data in a native binary format (similar to how STRUCTs are stored), enabling efficient indexing and querying via the `JSON` path expressions. In real-world scenarios, raw event logs from sources like web analytics or IoT devices often have unpredictable fields; using JSON allows ingestion without schema evolution, and later extraction of specific fields using `JSON_QUERY` or `JSON_VALUE` for BI dashboards.
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
Got this wrong? Here's your next step.
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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: JSON — Option D is correct because BigQuery's JSON data type is designed to store semistructured data with varying fields, such as raw event logs. It allows schema flexibility, efficient querying of nested fields using JSON functions like `JSON_EXTRACT`, and avoids the need to predefine a rigid schema, which is ideal for BI analysis of event payloads.
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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