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| Section | Weight | Objectives |
|---|---|---|
| Filtering and Formatting Results | 15% | - Sort, rename, and limit results - Use search and where commands - Use fillnull, eval, and other formatting commands |
| Creating and Using Field Aliases and Calculated Fields | 10% | - Create calculated fields with eval - Define and use field aliases - Manage field extractions and aliases |
| Creating Tags and Event Types | 10% | - Create and apply tags to fields or values - Use tags and event types in searches - Define event types to categorize events |
| Correlating Events | 15% | - Group events by fields and time - Compare transactions vs stats commands - Identify and use transactions |
| Transforming Commands and Visualizations | 15% | - Format results for presentation - Create and customize visualizations - Use transforming commands to structure data |
| Creating and Using Workflow Actions | 10% | - Use workflow actions to extend searches - Create and configure workflow actions - Describe GET, POST, and Search workflow actions |
| Using Macros | 10% | - Create and reuse search macros - Manage macro permissions and sharing - Add and use arguments in macros |
| Creating Data Models | 10% | - Create and use data models - Define data model objects and attributes - Understand data models and Pivot |
| Using the Common Information Model (CIM) Add-On | 5% | - Describe Splunk CIM purpose and structure - Normalize data using CIM knowledge objects - Use CIM to standardize data across sources |
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質問 # 100
What are the two parts of a root event dataset?
正解：D
解説：
Reference:https://docs.splunk.com/Documentation/SplunkLight/7.3.5/GettingStarted/Designdatamodelobjects
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.
質問 # 101
A data model consists of which three types of datasets?
正解：B
解説：
Explanation
Explanation/Reference: https://docs.splunk.com/Splexicon:Datamodeldataset
質問 # 102
When used with the timechart command, which value of the limit argument returns all values?
正解：D
解説：
The correct answer is D. limit=0. This is because the limit argument specifies the maximum number of series to display in the chart. If you set limit=0, no series filtering occurs and all values are returned. You can learn more about the limit argument and how it works with the agg argument from the Splunk documentation1. The other options are incorrect because they are not valid values for the limit argument. The limit argument expects an integer value, not a string or a wildcard. You can learn more about the syntax and usage of the timechart command from the Splunk documentation23.
質問 # 103
Which of the following statements describe the search string below?
| datamodel Application_State All_Application_State search
正解：C
質問 # 104
What approach is recommended when using the Splunk Common Information Model (CIM) add-on to normalize data?
正解：D
解説：
The recommended approach when using the Splunk Common Information Model (CIM) add-on to normalize data is A. Consult the CIM data model reference tables. This is because the CIM data model reference tables provide detailed information about the fields and tags that are expected for each dataset in a data model. By consulting the reference tables, you can determine which data models are relevant for your data source and how to map your data fields to the CIM fields. You can also use the reference tables to validate your data and troubleshoot any issues with normalization. You can find the CIM data model reference tables in the Splunk documentation1 or in the Data Model Editor page in Splunk Web2. The other options are incorrect because they are not related to the CIM add-on or data normalization. The authentication command is a custom command that validates events against the Authentication data model, but it does not help you to normalize other types of data. The correlation command is a search command that performs statistical analysis on event fields, but it does not help you to map your data fields to the CIM fields. The CIM event type reference tables do not exist, as event types are not part of the CIM add-on.
質問 # 105
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