- A
Schedule the data quality scan using Dataplex scheduling options
Dataplex allows scheduling data quality tasks (e.g., weekly) directly from the UI or API.
- B
Use Cloud DLP to inspect the table for data quality issues
Why wrong: Cloud DLP is for sensitive data inspection and de-identification, not for data quality checks like null checks or range validation.
- C
Create a column rule for the 'age' column using SQL condition 'age BETWEEN 0 AND 120'
Column rules can validate that all values in a column fall within a range. BETWEEN is appropriate.
- D
Create a Dataplex asset and add a tag template to enforce constraints
Why wrong: Tag templates are for metadata, not for data quality validation.
- E
Create a row rule for the 'email' column using SQL condition 'email IS NOT NULL'
A row rule can check a condition per row. 'IS NOT NULL' is a valid row-level check.
PDE Maintaining and Automating Data Workloads Practice Question
This PDE practice question tests your understanding of maintaining and automating data workloads. 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 data engineer needs to set up a Dataplex data quality scan to run weekly on a BigQuery table. The scan should check that: (1) the 'email' column is not null, (2) the 'age' column is between 0 and 120, and (3) the 'country_code' column matches a list of valid ISO codes. Which TWO Dataplex features should the engineer use?
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
Schedule the data quality scan using Dataplex scheduling options
Dataplex data quality tasks use SQL-based rules. Row rules validate conditions per row (e.g., IS NOT NULL, BETWEEN). Column rules validate column-level conditions (e.g., in set). Schedule is set via the scheduling feature. The other options are not Dataplex data quality features: DLP is for sensitive data, Data Catalog is for metadata.
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.
- ✓
Schedule the data quality scan using Dataplex scheduling options
Why this is correct
Dataplex allows scheduling data quality tasks (e.g., weekly) directly from the UI or API.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use Cloud DLP to inspect the table for data quality issues
Why it's wrong here
Cloud DLP is for sensitive data inspection and de-identification, not for data quality checks like null checks or range validation.
- ✓
Create a column rule for the 'age' column using SQL condition 'age BETWEEN 0 AND 120'
Why this is correct
Column rules can validate that all values in a column fall within a range. BETWEEN is appropriate.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Create a Dataplex asset and add a tag template to enforce constraints
Why it's wrong here
Tag templates are for metadata, not for data quality validation.
- ✓
Create a row rule for the 'email' column using SQL condition 'email IS NOT NULL'
Why this is correct
A row rule can check a condition per row. 'IS NOT NULL' is a valid row-level check.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
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.
- Use explanations to understand the rule behind the answer.
TExam Day Tips
- Underline the problem statement mentally.
- 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.
Identify which PDE exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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FAQ
Questions learners often ask
What does this PDE question test?
Maintaining and Automating Data Workloads — This question tests Maintaining and Automating Data Workloads — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Schedule the data quality scan using Dataplex scheduling options — Dataplex data quality tasks use SQL-based rules. Row rules validate conditions per row (e.g., IS NOT NULL, BETWEEN). Column rules validate column-level conditions (e.g., in set). Schedule is set via the scheduling feature. The other options are not Dataplex data quality features: DLP is for sensitive data, Data Catalog is for metadata.
What should I do if I get this PDE question wrong?
Identify which PDE exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jul 4, 2026
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