2024 Knowledge SPLK-1002 Points - High Pass-Rate Splunk Splunk Core Certified Power User Exam

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The Splunk SPLK-1002 certification exam is one of the hottest and career-oriented Splunk Core Certified Power User Exam (SPLK-1002) exams. With the Splunk Core Certified Power User Exam (SPLK-1002) exam you can validate your skills and upgrade your knowledge level. By doing this you can learn new in-demand skills and gain multiple career opportunities. To do this you just need to enroll in the Splunk SPLK-1002 Certification Exam and put all your efforts to pass this important Splunk SPLK-1002 Exam Questions.

Splunk SPLK-1002 (Splunk Core Certified Power User) Exam is a certification exam designed to test the knowledge and skills of individuals in using Splunk software to analyze and visualize machine-generated data. SPLK-1002 exam is intended for individuals who have already attained the Splunk Certified User certification and have experience working with Splunk software in a professional environment. SPLK-1002 exam is designed to validate the ability of the test-taker to use Splunk software to monitor, search, analyze, and visualize data.

Certification Path

Splunk Core Certified User is a recommended entry-level exam to Splunk Core Certified Power User. We encourage all candidates to become Splunk Core Certified Users as their first step in our certification program, though it is not required, Candidates can directly appear for Splunk Core Certified Power User splk-1002 Exam.

Splunk SPLK-1002 exam is an online, proctored exam that consists of 60 multiple-choice questions. Candidates have 90 minutes to complete the exam, and they must achieve a passing score of 70% or higher. SPLK-1002 exam can be taken at any time, and candidates can schedule the exam according to their availability.

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Splunk Core Certified Power User Exam Sample Questions (Q157-Q162):

NEW QUESTION # 157
If there are fields in the data with values that are " " or empty but not null, which of the following would add a value?

A. | eval notNULL = if(isnull (notNULL), "0" notNULL)
B. | eval notNULL = "" fillnull value=0 notNULL
C. | eval notNULL = "" | nullfill value=0 notNULL
D. | eval notNULL = if(isnull (notNULL), "0"

Answer: B

Explanation:
Explanation
The correct answer is D. | eval notNULL = "" fillnull value=0 notNULL
Option A is incorrect because it is missing a comma between the "0" and the notNULL in the if function. The correct syntax for the if function is if (condition, true_value, false_value).
Option B is incorrect because it is missing the false_value argument in the if function. The correct syntax for the if function is if (condition, true_value, false_value).
Option C is incorrect because it uses the nullfill command, which only replaces null values, not empty strings. The nullfill command is equivalent to fillnull value=null.
Option D is correct because it uses the eval command to assign an empty string to the notNULL field, and then uses the fillnull command to replace the empty string with a zero. The fillnull command can replace any value with a specified replacement, not just null values.

NEW QUESTION # 158
Which of the following statements about tags is true? (select all that apply.)

A. Tags are case-insensitive.
B. Tags are based on field/vale pairs.
C. Tags categorize events based on a search.
D. Tags are designed to make data more understandable.

Answer: B,D

Explanation:
The following statements about tags are true: tags are based on field/value pairs and tags categorize events based on a search. Tags are custom labels that can be applied to fields or field values to provide additional context or meaning for your data. Tags can be used to filter or analyze your data based on common concepts or themes. Tags can be created by using various methods, such as search commands, configuration files, user interfaces, etc. Some of the characteristics of tags are:
Tags are based on field/value pairs: This means that tags are associated with a specific field name and a specific field value. For example, you can create a tag called "alert" for the field name "status" and the field value "critical". This means that only events that have status=critical will have the "alert" tag applied to them.
Tags categorize events based on a search: This means that tags are defined by a search string that matches the events that you want to tag. For example, you can create a tag called "web" for the search string sourcetype=access_combined. This means that only events that match the search string sourcetype=access_combined will have the "web" tag applied to them.
The following statements about tags are false: tags are case-insensitive and tags are designed to make data more understandable. Tags are case-sensitive and tags are designed to make data more searchable. Tags are case-sensitive: This means that tags must match the exact case of the field name and field value that they are associated with. For example, if you create a tag called "alert" for the field name "status" and the field value "critical", it will not apply to events that have status=CRITICAL or Status=critical. Tags are designed to make data more searchable: This means that tags can help you find relevant events or patterns in your data by using common concepts or themes. For example, if you create a tag called "web" for the search string sourcetype=access_combined, you can use tag=web to find all events related to web activity.

NEW QUESTION # 159
Which of the following searches would create a graph similar to the one below?

index=_internal sourcetype=SavedSplunker | fields sourcetype, status |

A. transaction status maxspan=1d | chart count OVER status by _time
index=_internal sourcetype=SavedSplunker | fields sourcetype, status |
B. transaction status maxspan=1d | timechart count by status
C. None of these searches would generate a similar graph.
D. transaction status maxspan=1d | stats count by status
index=_internal sourcetype=SavedSplunker | fields sourcetype, status |

Answer: C

Explanation:
None of these functions related to the graph in exhibit. All of these functions have maxspan=ld which is not a valid argument.

NEW QUESTION # 160
Why would the transaction command be used instead of the stats command?

A. The transaction command can perform calculations on fields.
B. The transaction command has better search-time performance.
C. The transaction command keeps the raw data for each event.
D. The transaction command is less resource-intensive.

Answer: C

Explanation:
The transaction command is used when you need to group events and preserve the raw event data. This is essential in situations where context is important and you need to maintain the original details of each event.
References:
Splunk Docs - transaction command
Splunk Answers - When to use transaction vs stats

NEW QUESTION # 161
Which of the following describes the Splunk Common Information Model (CIM) add-on?

A. The CIM add-on uses machine learning to normalize data.
B. The CIM add-on contains data models to help you normalize data.
C. The CIM add-on is automatically installed in a Splunk environment.
D. The CIM add-on contains dashboards that show how to map data.

Answer: B

Explanation:
The Splunk Common Information Model (CIM) add-on is a Splunk app that contains data models to help you normalize data from different sources and formats. The CIM add-on defines a common and consistent way of naming and categorizing fields and events in Splunk. This makes it easier to correlate and analyze data across different domains, such as network, security, web, etc. The CIM add-on does not use machine learning to normalize data, but rather relies on predefined field names and values. The CIM add-on does not contain dashboards that show how to map data, but rather provides documentation and examples on how to use the data models. The CIM add-on is not automatically installed in a Splunk environment, but rather needs to be downloaded and installed from Splunkbase.

NEW QUESTION # 162
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