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| Section | Weight | Objectives |
|---|
| Filtering and Formatting Results | 15% | - Use fillnull, eval, and other formatting commands - Use search and where commands - Sort, rename, and limit results
|
| Correlating Events | 15% | - Identify and use transactions - Compare transactions vs stats commands - Group events by fields and time
|
| Using Macros | 10% | - Manage macro permissions and sharing - Add and use arguments in macros - Create and reuse search macros
|
| Using the Common Information Model (CIM) Add-On | 5% | - Normalize data using CIM knowledge objects - Describe Splunk CIM purpose and structure - Use CIM to standardize data across sources
|
| Creating Tags and Event Types | 10% | - Define event types to categorize events - Create and apply tags to fields or values - Use tags and event types in searches
|
| Creating and Using Workflow Actions | 10% | - Use workflow actions to extend searches - Describe GET, POST, and Search workflow actions - Create and configure workflow actions
|
| Creating and Using Field Aliases and Calculated Fields | 10% | - Define and use field aliases - Manage field extractions and aliases - Create calculated fields with eval
|
| Creating Data Models | 10% | - Understand data models and Pivot - Define data model objects and attributes - Create and use data models
|
| Transforming Commands and Visualizations | 15% | - Create and customize visualizations - Format results for presentation - Use transforming commands to structure data
|
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Splunk Core Certified Power User Exam Sample Questions (Q253-Q258):
NEW QUESTION # 253
What are the two parts of a root event dataset?
- A. Constraints and lookups.
- B. Fields and variables.
- C. Constraints and fields.
- D. Fields and attributes.
Answer: C
Explanation:
Reference:
A root event dataset is the base dataset for a data model that defines the source or sources of the data and the constraints and fields that apply to the data1. A root event dataset has two parts: constraints and fields1. Constraints are filters that limit the data to a specific index, source, sourcetype, host or search string1. Fields are the attributes that describe the data and can be extracted, calculated or looked up1. Therefore, option C is correct, while options A, B and D are incorrect.
NEW QUESTION # 254
Which search commands allow a user to access data model summaries?
- A. transaction, tstats, and datamodel
- B. stats, tstats, and datamodel
- C. pivot, tstats, and datamodel
- D. pivot, stats, and datamodel
Answer: C
Explanation:
The commands pivot and tstats both leverage data model summaries for faster search performance. The datamodel command itself is used to inspect or operate on data models. The transaction and stats commands do not directly access data model summaries.
Reference:
Splunk Power User Study Guide, Data Models and Pivot
Splunk Docs: tstats Command, pivot Command
"Both pivot and tstats are optimized to work with data model summaries for high-speed queries."
NEW QUESTION # 255
Which of the following statements describes POST workflow actions?
- A. POST workflow actions can be configured to send POST arguments to the URI location.
- B. By default, POST workflow action are shown in both the event and field menus.
- C. POST workflow actions can be configured to send email to the URI location.
- D. Configuration of a POST workflow action includes choosing a sourcetype.
Answer: D
NEW QUESTION # 256
Why are tags useful in Splunk?
- A. Tags visualize data with graphs and charts.
- B. Tags look for less specific data.
- C. Tags add fields to the raw event data.
- D. Tags group related data together.
Answer: D
Explanation:
Tags are a type of knowledge object that enable you to assign descriptive keywords to events based on the values of their fields. Tags can help you to search more efficiently for groups of event data that share common characteristics, such as functionality, location, priority, etc. For example, you can tag all the IP addresses of your routers as router, and then search for tag=router to find all the events related to your routers. Tags can also help you to normalize data from different sources by using the same tag name for equivalent field values. For example, you can tag the field values error, fail, and critical as severity=high, and then search for severity=high to find all the events with high severity level2
1: Splunk Core Certified Power User Track, page 10. 2: Splunk Documentation, About tags and aliases.
NEW QUESTION # 257
What does the following search do?

- A. Creates a table that groups the total number of users by vegetarian corndogs.
- B. Creates a table of the total count of users and split by corndogs.
- C. Creates a table of the total count of mysterymeat corndogs split by user.
- D. Creates a table with the count of all types of corndogs eaten split by user.
Answer: C
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 # 258
......
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