Quick Answer
The answer is to create a view that selects specific columns. This is the best practice for BI dashboard query optimization because views enable column pruning at the query level, reducing I/O and memory consumption by avoiding full table scans on unnecessary columns from the underlying large table. On the Google Professional Cloud Database Engineer exam, this scenario tests your understanding of logical abstraction layers and performance tuning without altering schema—a common trap is assuming you must redesign the table or use materialized views, but a simple view provides the necessary column restriction while preserving data integrity and access control. Remember the memory tip: “View the columns you need, not the table you feed.”
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 BI dashboard query is taking too long because it reads all columns from a large table. The dashboard only needs a few columns. What is the best practice?
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.
Create a view that selects specific columns.
Views with column selection allow column pruning.
Create a table with only the needed columns.
Why wrong: This duplicates data and incurs storage costs.
Use a subquery to filter columns in the FROM clause.
Why wrong: BigQuery may still scan all columns if the subquery is not materialized.
Use a LIMIT clause to reduce rows.
Why wrong: LIMIT does not reduce columns scanned.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Create a view that selects specific columns.
Creating a view that selects specific columns is the best practice because it allows the BI dashboard to query only the necessary columns without altering the underlying table structure. Views provide a logical abstraction layer, enabling column pruning at the query level while preserving data integrity and access control. This approach reduces I/O and memory consumption by avoiding full table scans on unnecessary columns, directly addressing the performance bottleneck.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Create a view that selects specific columns.
Why this is correct
Views with column selection allow column pruning.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
Create a table with only the needed columns.
Why it's wrong here
This duplicates data and incurs storage costs.
Use a subquery to filter columns in the FROM clause.
Why it's wrong here
BigQuery may still scan all columns if the subquery is not materialized.
Use a LIMIT clause to reduce rows.
Why it's wrong here
LIMIT does not reduce columns scanned.
Common exam traps
Google Cloud often tests the misconception that a subquery or LIMIT can optimize column-level performance, when in fact they only affect row filtering or query structure, not the column scan width.
Detailed technical explanation
Under the hood, a view in PostgreSQL (and most RDBMSs) acts as a stored query that the optimizer can inline and optimize, potentially using index-only scans if the selected columns are indexed. In real-world BI scenarios, column pruning via views can reduce network transfer and memory allocation significantly, especially when dealing with wide tables containing hundreds of columns. However, note that materialized views would physically store data and could become stale, whereas a regular view always reflects the latest data without duplication.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A company's IT admin needs to give a contractor read-only access to production logs without sharing account credentials. Using role-based access control (RBAC) and temporary scoped permissions — not a permanent shared password — is the correct pattern. Questions like this test whether you can apply least-privilege access across cloud identity services.
What to study next
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FAQ
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..
The correct answer is: Create a view that selects specific columns. — Creating a view that selects specific columns is the best practice because it allows the BI dashboard to query only the necessary columns without altering the underlying table structure. Views provide a logical abstraction layer, enabling column pruning at the query level while preserving data integrity and access control. This approach reduces I/O and memory consumption by avoiding full table scans on unnecessary columns, directly addressing the performance bottleneck.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 30, 2026
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