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| Section | Weight | Objectives |
|---|
| Topic 1: Creating Data Models | 10% | - Create and use data models - Understand data models and Pivot - Define data model objects and attributes
|
| Topic 2: Creating and Using Field Aliases and Calculated Fields | 10% | - Manage field extractions and aliases - Define and use field aliases - Create calculated fields with eval
|
| Topic 3: Filtering and Formatting Results | 15% | - Use search and where commands - Sort, rename, and limit results - Use fillnull, eval, and other formatting commands
|
| Topic 4: Using the Common Information Model (CIM) Add-On | 5% | - Describe Splunk CIM purpose and structure - Use CIM to standardize data across sources - Normalize data using CIM knowledge objects
|
| Topic 5: Creating and Using Workflow Actions | 10% | - Describe GET, POST, and Search workflow actions - Use workflow actions to extend searches - Create and configure workflow actions
|
| Topic 6: Using Macros | 10% | - Create and reuse search macros - Add and use arguments in macros - Manage macro permissions and sharing
|
| Topic 7: Correlating Events | 15% | - Identify and use transactions - Compare transactions vs stats commands - Group events by fields and time
|
| Topic 8: Transforming Commands and Visualizations | 15% | - Create and customize visualizations - Use transforming commands to structure data - Format results for presentation
|
| Topic 9: 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
|
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Splunk Core Certified Power User Exam Sample Questions (Q100-Q105):
NEW QUESTION # 100
Which field extraction method should be selected for comma-separated data?
- A. table extraction
- B. Regular expression
- C. Delimiters
- D. eval expression
Answer: C
Explanation:
The correct answer is B. Delimiters. This is because the delimiters method is designed for structured event
data, such as data from files with headers, where all of the fields in the events are separated by a common
delimiter, such as a comma or space. You can select a sample event, identify the delimiter, and then rename
the fields that the field extractor finds.You can learn more about the delimiters method from the Splunk
documentation1. The other options are incorrect because they are not suitable for comma-separated data. The
regular expression method works best with unstructured event data, where you select and highlight one or
more fields to extract from a sample event, and the field extractor generates a regular expression that matches
similar events and extracts the fields from them. The eval expression is a command that lets you calculate new
fields or modify existing fields using arithmetic, string, and logical operations. The table extraction is a feature
that lets you extract tabular data from PDF files or web pages.You can learn more about these methods from
the Splunk documentation23.
NEW QUESTION # 101
What is the relationship between data models and pivots?
- A. Pivots and data models are the same thing.
- B. Pivots provide the datasets for data models.
- C. Pivots and data models have no relationship.
- D. Data models provide the datasets for pivots.
Answer: D
Explanation:
The relationship between data models and pivots is that data models provide the datasets for pivots. Data
models are collections of datasets that represent your data in a structured and hierarchical way. Data models
define how your data is organized into objects and fields. Pivots are user interfaces that allow you to create
data visualizations that present different aspects of a data model. Pivots let you select options from menus and
forms to create charts, tables, maps, etc., without writing any SPL code. Pivots use datasets from data models
as their source of data. Pivots and data models are not the same thing, as pivots are tools for visualizing data
models. Pivots do not provide datasets for data models, but rather use them as inputs.
Therefore, only statement A is true about the relationship between data models and pivots.
NEW QUESTION # 102
What type of command is eval?
- A. Distributable streaming
- B. Streaming in some modes
- C. Report generating
- D. Centralized streaming
Answer: A
Explanation:
The correct answer is C. Distributable streaming. This is because the eval command is a type of command that can run on the indexers before the results are sent to the search head. This reduces the amount of data that needs to be transferred and improves the search performance. Distributable streaming commands can operate on each event or result individually, without depending on other events or results. You can learn more about the types of commands and how they affect search performance from the Splunk documentation1.
NEW QUESTION # 103
which of the following commands are used when creating visualizations(select all that apply.)
- A. Geom
- B. Choropleth
- C. Geostats
- D. iplocation
Answer: A,C,D
NEW QUESTION # 104
What does the fillnull command do in this search?
index=main sourcetype=http:log | fillnull value="Unknown" src
- A. Set the values of the src field to "Unknown" if it is null.
- B. Set the values of the src field to null when it is "Unknown".
- C. Set all fields with the value of "Unknown" to null.
- D. Set all fields that are null to "Unknown".
Answer: A
Explanation:
The fillnull command replaces null or missing values in specified fields with a given replacement value. In this example, the command sets the src field to "Unknown" wherever it is null. It does not affect other fields or convert values from "Unknown" back to null.
Reference:
Splunk Power User Study Guide, Search Commands Section
Splunk Docs: fillnull Command
"fillnull replaces null field values with a specified string or number for a given field or fields."
NEW QUESTION # 105
......
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