Learning Splunk - Normalizing Data Using the Splunk Common Information Model (CIM)

Learning Splunk - Normalizing Data Using the Splunk Common Information Model (CIM)

Assessment

Interactive Video

Information Technology (IT), Architecture, Business, Social Studies

University

Hard

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The video tutorial explains how to normalize data using Splunk's Common Information Model (CIM). It highlights the default behavior of Splunk in extracting fields based on key-value pairs and the challenges posed by inconsistent logging across different firewalls. The tutorial introduces CIM as a solution to standardize field names, making data easily searchable and accessible. It also demonstrates how CIM can be applied to network traffic data, ensuring consistency and predictability in field names regardless of the vendor.

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5 questions

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1.

OPEN ENDED QUESTION

3 mins • 1 pt

What is the default behavior of Splunk when extracting fields from logs?

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2.

OPEN ENDED QUESTION

3 mins • 1 pt

What are some examples of how a source IP address might be represented differently in logs?

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3.

OPEN ENDED QUESTION

3 mins • 1 pt

Why is consistency important when dealing with field names in Splunk?

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4.

OPEN ENDED QUESTION

3 mins • 1 pt

How does the Common Information Model (CIM) help in normalizing data?

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5.

OPEN ENDED QUESTION

3 mins • 1 pt

What are the expected values for the action field in the Common Information Model?

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