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NEW QUESTION # 82
What is the purpose of using data models in building dashboards?
Answer: A
Explanation:
Why Use Data Models in Dashboards?
SplunkData Modelsallow dashboards toretrieve structured, normalized data quickly, improving search performance and accuracy.
#How Data Models Help in Dashboards?(AnswerB)#Standardized Field Naming- Ensures that queries always useconsistent field names(e.g.,src_ipinstead ofsource_ip).#Faster Searches- Data models allow dashboards torun structured searches instead of raw log queries.#Example:ASOC dashboard for user activity monitoringuses a CIM-compliantAuthentication Data Model, ensuring that querieswork across different log sources.
Why Not the Other Options?
#A. To store raw data for compliance purposes- Raw data is stored in indexes,not data models.#C. To compress indexed data- Data modelsstructuredata but donot perform compression.#D. To reduce storage usage on Splunk instances- Data modelshelp with search performance, not storage reduction.
References & Learning Resources
#Splunk Data Models for Dashboard Optimization: https://docs.splunk.com/Documentation/Splunk/latest
/Knowledge/Aboutdatamodels#Building Efficient Dashboards Using Data Models: https://splunkbase.splunk.
com#Using CIM-Compliant Data Models for Security Analytics: https://www.splunk.com/en_us/blog/tips- and-tricks
NEW QUESTION # 83
Which practices improve the effectiveness of security reporting?(Choosethree)
Answer: A,D,E
Explanation:
Effective security reporting helps SOC teams, executives, and compliance officers make informed decisions.
#1. Automating Report Generation (A)
Saves time by scheduling reports for regular distribution.
Reduces manual effort and ensures timely insights.
Example:
A weekly phishing attack report sent to SOC analysts.
#2. Customizing Reports for Different Audiences (B)
Technical reports for SOC teams include detailed event logs.
Executive summaries provide risk assessments and trends.
Example:
SOC analysts see incident logs, while executives get a risk summary.
#3. Providing Actionable Recommendations (D)
Reports should not just show data but suggest actions.
Example:
If failed login attempts increase, recommend MFA enforcement.
#Incorrect Answers:
C: Including unrelated historical data for context # Reports should be concise and relevant.
E: Using dynamic filters for better analysis # Useful in dashboards, but not a primary factor in reporting effectiveness.
#Additional Resources:
Splunk Security Reporting Guide
Best Practices for Security Metrics
NEW QUESTION # 84
Which methodology prioritizes risks by evaluating both their likelihood and impact?
Answer: C
Explanation:
Understanding Risk-Based Prioritization
Risk-based prioritization is a methodology that evaluatesboth the likelihood and impact of risksto determine which threats require immediate action.
#Why Risk-Based Prioritization?
Focuses onhigh-impact and high-likelihoodrisks first.
HelpsSOC teams manage alerts effectivelyand avoid alert fatigue.
Used inSIEM solutions (Splunk ES) and Risk-Based Alerting (RBA).
Example in Splunk Enterprise Security (ES):
Afailed login attemptfrom aninternal employeemight below risk(low impact, low likelihood).
Multiple failed loginsfrom aforeign countrywith a knownbad reputationcould behigh risk(high impact, high likelihood).
#Incorrect Answers:
A: Threat modeling# Identifies potential threats but doesn'tprioritize risks dynamically.
C: Incident lifecycle management# Focuses on handling security incidents, notrisk evaluation.
D: Statistical anomaly detection# Detects unusual activity but doesn'tprioritize based on impact.
#Additional Resources:
Splunk Risk-Based Alerting (RBA) Guide
NIST Risk Assessment Framework
NEW QUESTION # 85
Which Splunk configuration ensures events are parsed and indexed only once for optimal storage?
Answer: C
Explanation:
Why Use Index-Time Transformations for One-Time Parsing & Indexing?
Splunk parses and indexes data once during ingestion to ensure efficient storage and search performance.
Index-time transformations ensure that logs are:
#Parsed, transformed, and stored efficiently before indexing.#Normalized before indexing, so the SOC team doesn't need to clean up fields later.#Processed once, ensuring optimal storage utilization.
#Example of Index-Time Transformation in Splunk:#Scenario: The SOC team needs to mask sensitive data in security logs before storing them in Splunk.#Solution: Use anINDEXED_EXTRACTIONSrule to:
Redact confidential fields (e.g., obfuscate Social Security Numbers in logs).
Rename fields for consistency before indexing.
NEW QUESTION # 86
What does Splunk's term "bucket" refer to in data indexing?
Answer: C
NEW QUESTION # 87
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