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Splunk SPLK-1002 Exam Syllabus Topics:

Section	Weight	Objectives
Workflow Actions	10%	- Workflow action types 1. POST workflow actions 2. Search workflow actions 3. GET workflow actions
Using Transforming Commands for Visualizations	5%	- Visualization commands 1. chart command 2. timechart command
Filtering and Formatting Results	10%	- Search and evaluation commands 1. where command 2. search command 3. fillnull command 4. eval command
Macros	10%	- Search macros 1. Macros with arguments 2. Create and use basic macros
Tags and Event Types	10%	- Knowledge objects 1. Event types usage 2. Create event types 3. Create and use tags
Correlating Events	15%	- Event correlation techniques 1. Group events using fields and time 2. Group events using fields 3. Report on transactions 4. Search with transactions 5. Identify transactions 6. When to use transactions vs stats
Field Aliases and Calculated Fields	10%	- Field enrichment 1. Calculated fields 2. Field aliases
Creating and Managing Fields	10%	- Field extraction methods 1. Delimiter field extraction using Field Extractor (FX) 2. Regex field extraction using Field Extractor (FX)
Common Information Model (CIM)	10%	- Data normalization 1. Using CIM add-ons 2. Purpose of CIM 3. Data normalization techniques
Data Models	10%	- Data model concepts 1. Create data models 2. Data model attributes 3. Data model structure 4. Pivot usage

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Splunk Core Certified Power User Exam Sample Questions (Q298-Q303):

NEW QUESTION # 298
What do events in a transaction have In common?

A. All events in a transaction must be related by one or more fields.
B. All events In a transaction must have the same timestamp.
C. All events in a transaction must have the same sourcetype.
D. All events in a transaction must have the exact same set of fields.

Answer: A

Explanation:
Reference: https://docs.splunk.com/Documentation/Splunk/8.0.3/Knowledge/Abouttransactions A transaction is a group of events that share some common characteristics, such as fields, time, or both. A transaction can be created by using the transaction command or by defining an event type with transactiontype=true in props.conf. Events in a transaction have one or more fields in common that relate them to each other. For example, you can create a transaction based on JSESSIONID, which is a unique identifier for each user session in web logs. Events in a transaction do not have to have the same timestamp, sourcetype, or exact same set of fields. They only have to share one or more fields that define the transaction.

NEW QUESTION # 299
Which of the following eval commands will provide a new value for host from src if it exists?

A. | eval host = if (NOT src = host, src, host)
B. | eval host = if (src = host, src, host)
C. | eval host = if (isnotnull (src), src, host)
D. | eval host = if (isnu11 (src), src, host)

Answer: C

Explanation:
The eval command is a Splunk command that allows you to create or modify fields using expressions .
The if function is an expression that evaluates a condition and returns a value based on whether the
condition is true or false. The syntax of the if function is if(X,Y,Z), where X is the condition, Y is the
value to return if X is true, and Z is the value to return if X is false.
The isnotnull function is an expression that returns true if the argument is not null, and false otherwise.
The syntax of the isnotnull function is isnotnull(X), where X is the argument to check.
Therefore, the expression if (isnotnull (src), src, host) returns the value of src if it is not null, and the
value of host otherwise. This means that it will provide a new value for host from src if it exists, and
keep the original value of host otherwise.

NEW QUESTION # 300
Data model fields can be added using the Auto-Extracted method.
Which of the following statements describe Auto-Extracted fields? (Choose all that apply.)

A. Auto-Extracted fields can be added if they already exist in the dataset with constraints.
B. Auto-Extracted fields can have their data type changed.
C. Auto-Extracted fields can be given a friendly name for use in Pivot.
D. Auto-Extracted fields can be hidden in Pivot.

Answer: B

NEW QUESTION # 301
When using the Field Extractor (FX), which of the following delimiters will work? (select all that apply)

A. Spaces
B. Pipes
C. Colons
D. Tabs

Answer: A,B,D

Explanation:
Reference:
https://community.splunk.com/t5/Splunk-Search/Field-Extraction-Separate-on-Colon/m-p/29751 The Field Extractor (FX) is a tool that helps you extract fields from your data using delimiters or regular expressions. Delimiters are characters or strings that separate fields in your data. Some of the delimiters that will work with FX are:
Tabs: horizontal spaces that align text in columns.
Pipes: vertical bars that often indicate logical OR operations.
Spaces: blank characters that separate words or symbols.
Therefore, the delimiters A, B, and D will work with FX.

NEW QUESTION # 302
What does the following search do?

A. Creates a table of the total count of users and split by corndogs.
B. Creates a table that groups the total number of users by vegetarian corndogs.
C. Creates a table with the count of all types of corndogs eaten split by user.
D. Creates a table of the total count of mysterymeat corndogs split by user.

Answer: D

Explanation:
The search string below creates a table of the total count of mysterymeat corndogs split by user.
| stats count by user | where corndog=mysterymeat
The search string does the following:
* It uses the stats command to calculate the count of events for each value of the user field. The stats command creates a table with two columns: user and count.
* It uses the where command to filter the results by the value of the corndog field. The where command only keeps the rows where corndog equals mysterymeat.
Therefore, the search string creates a table of the total count of mysterymeat corndogs split by user.

NEW QUESTION # 303
......

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