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Question 780
Network traffic is logged by firewalls, routers, and endpoint sensors. In this extended practice exercise, which THREE statements about the required Splunk behavior are correct? Choose THREE.
- Normalize equivalent source fields to one common semantic vocabulary
- Assume all security tools use identical raw field names and need no normalization
- Discard sourcetype information immediately after mapping to CIM
- Map each source's classification to the appropriate data model population
- Compare a cloud authentication name with a router interface name as though they represent identical user identities
- Cross-check a shared query using examples from each supported source
Explanation
Correct Answers
A:Consistent fields allow cross-product reporting.
D:Related events must meet model constraints.
F:Validation reveals missing integration paths.
Incorrect Answers
B:Vendors commonly use different schemas.
C:Provenance remains useful.
E:A common data model requires semantic equivalence.
Question 781
A compliance dashboard uses a CIM model but some required fields are always blank. Which Splunk approach is technically appropriate for this need?
- Assume a required field will be populated solely because the matching event was tagged
- Invent missing destination addresses from the analyst's workstation IP
- Treat a dashboard column heading as proof the field was extracted from every event
- Check the model's defined required fields and tag constraints
Explanation
Correct Answer
D:CIM data-model reference tables document expectations.
Incorrect Answers
A:Tags do not synthesize an absent field.
B:Source facts cannot be guessed safely.
C:Column labels do not establish field availability.
Question 782
A compliance dashboard uses a CIM model but some required fields are always blank. Which implementation detail accurately describes the required behavior?
- Treat a dashboard column heading as proof the field was extracted from every event
- Resolve field gaps by deleting unrelated model constraints without evaluating membership impact
- Inspect source extractions and aliases that populate the missing normalized attributes
- Invent missing destination addresses from the analyst's workstation IP
Explanation
Correct Answer
C:Field mapping is a common root cause.
Incorrect Answers
A:Column labels do not establish field availability.
B:Blind changes can break data population.
D:Source facts cannot be guessed safely.
Question 783
A compliance dashboard uses a CIM model but some required fields are always blank. Which validation or design decision would make the result reliable?
- Assume a required field will be populated solely because the matching event was tagged
- Test a raw event, an extracted event, and its model dataset result to isolate the gap
- Resolve field gaps by deleting unrelated model constraints without evaluating membership impact
- Invent missing destination addresses from the analyst's workstation IP
Explanation
Correct Answer
B:Stepwise validation shows where normalization fails.
Incorrect Answers
A:Tags do not synthesize an absent field.
C:Blind changes can break data population.
D:Source facts cannot be guessed safely.
Question 784
A compliance dashboard uses a CIM model but some required fields are always blank. Which explanation best preserves the intended data meaning or control?
- Resolve field gaps by deleting unrelated model constraints without evaluating membership impact
- Keep a record of source-specific exceptions or optional fields where applicable
- Treat a dashboard column heading as proof the field was extracted from every event
- Assume a required field will be populated solely because the matching event was tagged
Explanation
Correct Answer
B:A trustworthy model documents its actual coverage.
Incorrect Answers
A:Blind changes can break data population.
C:Column labels do not establish field availability.
D:Tags do not synthesize an absent field.
Question 785
A compliance dashboard uses a CIM model but some required fields are always blank. In this extended practice exercise, which TWO statements about the required Splunk behavior are correct? Choose TWO.
- Resolve field gaps by deleting unrelated model constraints without evaluating membership impact
- Test a raw event, an extracted event, and its model dataset result to isolate the gap
- Check the model's defined required fields and tag constraints
- Invent missing destination addresses from the analyst's workstation IP
- Treat a dashboard column heading as proof the field was extracted from every event
Explanation
Correct Answers
B:Stepwise validation shows where normalization fails.
C:CIM data-model reference tables document expectations.
Incorrect Answers
A:Blind changes can break data population.
D:Source facts cannot be guessed safely.
E:Column labels do not establish field availability.
Question 786
A threat hunting query gets traffic dataset rows but cannot identify destination address. Which Splunk approach is technically appropriate for this need?
- Test a raw event, an extracted event, and its model dataset result to isolate the gap, but resolve field gaps by deleting unrelated model constraints without evaluating membership impact
- Check the model's defined required fields and tag constraints, but treat a dashboard column heading as proof the field was extracted from every event
- Inspect source extractions and aliases that populate the missing normalized attributes, but invent missing destination addresses from the analyst's workstation IP
- Check the model's defined required fields and tag constraints, and inspect source extractions and aliases that populate the missing normalized attributes
Explanation
Correct Answer
D:The two controls work together: CIM data-model reference tables document expectations. Field mapping is a common root cause.
Incorrect Answers
A:The first clause can be sound, but the second is not: Blind changes can break data population.
B:The first clause can be sound, but the second is not: Column labels do not establish field availability.
C:The first clause can be sound, but the second is not: Source facts cannot be guessed safely.
Question 787
A threat hunting query gets traffic dataset rows but cannot identify destination address. Which implementation detail accurately describes the required behavior?
- Keep a record of source-specific exceptions or optional fields where applicable, but assume a required field will be populated solely because the matching event was tagged
- Inspect source extractions and aliases that populate the missing normalized attributes, and test a raw event, an extracted event, and its model dataset result to isolate the gap
- Test a raw event, an extracted event, and its model dataset result to isolate the gap, but resolve field gaps by deleting unrelated model constraints without evaluating membership impact
- Inspect source extractions and aliases that populate the missing normalized attributes, but invent missing destination addresses from the analyst's workstation IP
Explanation
Correct Answer
B:The two controls work together: Field mapping is a common root cause. Stepwise validation shows where normalization fails.
Incorrect Answers
A:The first clause can be sound, but the second is not: Tags do not synthesize an absent field.
C:The first clause can be sound, but the second is not: Blind changes can break data population.
D:The first clause can be sound, but the second is not: Source facts cannot be guessed safely.
Question 788
A threat hunting query gets traffic dataset rows but cannot identify destination address. Which validation or design decision would make the result reliable?
- Test a raw event, an extracted event, and its model dataset result to isolate the gap, but resolve field gaps by deleting unrelated model constraints without evaluating membership impact
- Keep a record of source-specific exceptions or optional fields where applicable, but assume a required field will be populated solely because the matching event was tagged
- Check the model's defined required fields and tag constraints, but treat a dashboard column heading as proof the field was extracted from every event
- Test a raw event, an extracted event, and its model dataset result to isolate the gap, and keep a record of source-specific exceptions or optional fields where applicable
Explanation
Correct Answer
D:The two controls work together: Stepwise validation shows where normalization fails. A trustworthy model documents its actual coverage.
Incorrect Answers
A:The first clause can be sound, but the second is not: Blind changes can break data population.
B:The first clause can be sound, but the second is not: Tags do not synthesize an absent field.
C:The first clause can be sound, but the second is not: Column labels do not establish field availability.
Question 789
A threat hunting query gets traffic dataset rows but cannot identify destination address. Which explanation best preserves the intended data meaning or control?
- Keep a record of source-specific exceptions or optional fields where applicable, and check the model's defined required fields and tag constraints
- Check the model's defined required fields and tag constraints, but treat a dashboard column heading as proof the field was extracted from every event
- Keep a record of source-specific exceptions or optional fields where applicable, but assume a required field will be populated solely because the matching event was tagged
- Inspect source extractions and aliases that populate the missing normalized attributes, but invent missing destination addresses from the analyst's workstation IP
Explanation
Correct Answer
A:The two controls work together: A trustworthy model documents its actual coverage. CIM data-model reference tables document expectations.
Incorrect Answers
B:The first clause can be sound, but the second is not: Column labels do not establish field availability.
C:The first clause can be sound, but the second is not: Tags do not synthesize an absent field.
D:The first clause can be sound, but the second is not: Source facts cannot be guessed safely.
Question 790
A threat hunting query gets traffic dataset rows but cannot identify destination address. In this extended practice exercise, which THREE statements about the required Splunk behavior are correct? Choose THREE.
- Check the model's defined required fields and tag constraints
- Inspect source extractions and aliases that populate the missing normalized attributes
- Invent missing destination addresses from the analyst's workstation IP
- Assume a required field will be populated solely because the matching event was tagged
- Resolve field gaps by deleting unrelated model constraints without evaluating membership impact
- Keep a record of source-specific exceptions or optional fields where applicable
Explanation
Correct Answers
A:CIM data-model reference tables document expectations.
B:Field mapping is a common root cause.
F:A trustworthy model documents its actual coverage.
Incorrect Answers
C:Source facts cannot be guessed safely.
D:Tags do not synthesize an absent field.
E:Blind changes can break data population.
Splunk Core Certified Power User (SPLK-1002) Practice Tests
