- A
Delete PII fields from the data model
Why wrong: Reduces predictive power of the model unnecessarily.
- B
Use Calculated Insights to aggregate sensitive data only
Why wrong: Still exposes underlying PII in raw data.
- C
Apply data masking and field-level security on sensitive fields
Protects PII while preserving data utility.
- D
Rely on user permissions to restrict access to the entire object
Why wrong: User permissions are too coarse; field-level security is needed.
Question 92 of 1,000
AI Associate Data for AI Practice Question
This AI Associate practice question tests your understanding of data for ai. 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 financial institution must ensure that customer data used for AI models does not expose personally identifiable information (PII) to unauthorized users. Which Data Cloud feature should be applied to the data model?
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
✓
Apply data masking and field-level security on sensitive fields
Option C is correct because Data Cloud's data masking and field-level security features allow the institution to obscure PII at the field level while retaining its analytical value for AI models. Option A is incorrect because deleting PII fields permanently removes potentially valuable data and is not a scalable approach. Option B is incorrect; Calculated Insights are used to create aggregated metrics from raw data, but they do not prevent unauthorized users from viewing the underlying sensitive data. Option D is incorrect because object-level permissions alone cannot restrict access to specific fields; sensitive fields would be exposed to any user with object access.
Key principle: Count usable hosts — not total addresses — and remember that the network and broadcast addresses are not available to hosts in standard IPv4 subnets.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Delete PII fields from the data model
Why it's wrong here
Reduces predictive power of the model unnecessarily.
- ✗
Use Calculated Insights to aggregate sensitive data only
Why it's wrong here
Still exposes underlying PII in raw data.
- ✓
Apply data masking and field-level security on sensitive fields
Why this is correct
Protects PII while preserving data utility.
Related concept
CIDR notation defines the prefix length.
- ✗
Rely on user permissions to restrict access to the entire object
Why it's wrong here
User permissions are too coarse; field-level security is needed.
Common exam traps
Common exam trap: usable hosts are not the same as total addresses
Subnetting questions often tempt you into counting all addresses. In normal IPv4 subnets, the network and broadcast addresses are not usable host addresses.
Detailed technical explanation
How to think about this question
Subnetting questions test whether you can identify the network, broadcast address, usable range, mask and correct subnet. Slow down enough to calculate the block size correctly.
KKey Concepts to Remember
- CIDR notation defines the prefix length.
- Block size helps identify subnet boundaries.
- Network and broadcast addresses are not usable hosts in normal IPv4 subnets.
- The required host count determines the smallest suitable subnet.
TExam Day Tips
- Write the block size before choosing the subnet.
- Check whether the question asks for hosts, subnets or a specific address range.
- Do not confuse /24, /25, /26 and /27 host counts.
Key takeaway
Count usable hosts — not total addresses — and remember that the network and broadcast addresses are not available to hosts in standard IPv4 subnets.
Real-world example
How this comes up in practice
A network engineer segments a warehouse floor into three subnets: 20 scanners, 5 printers, and 2 management hosts. Picking the wrong mask wastes addresses or leaves too few usable hosts. Exam questions test whether you can apply CIDR notation, calculate block size, and identify the correct usable-host range for a given prefix.
What to study next
Got this wrong? Here's your next step.
Review block sizes, usable host formulas (2^n − 2), and how to find network and broadcast addresses for /24 through /30. Then practise related AI Associate subnetting questions on CIDR, address ranges, and subnet selection.
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FAQ
Questions learners often ask
What does this AI Associate question test?
Data for AI — This question tests Data for AI — CIDR notation defines the prefix length..
What is the correct answer to this question?
The correct answer is: Apply data masking and field-level security on sensitive fields — Option C is correct because Data Cloud's data masking and field-level security features allow the institution to obscure PII at the field level while retaining its analytical value for AI models. Option A is incorrect because deleting PII fields permanently removes potentially valuable data and is not a scalable approach. Option B is incorrect; Calculated Insights are used to create aggregated metrics from raw data, but they do not prevent unauthorized users from viewing the underlying sensitive data. Option D is incorrect because object-level permissions alone cannot restrict access to specific fields; sensitive fields would be exposed to any user with object access.
What should I do if I get this AI Associate question wrong?
Review block sizes, usable host formulas (2^n − 2), and how to find network and broadcast addresses for /24 through /30. Then practise related AI Associate subnetting questions on CIDR, address ranges, and subnet selection.
What is the key concept behind this question?
CIDR notation defines the prefix length.
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Last reviewed: Jun 23, 2026
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