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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Creating and Managing Fields | 10% | - Perform delimiter field extractions using the FX - Perform regex field extractions using the Field Extractor (FX) |
| Topic 2: Correlating Events | 15% | - Identify transactions - Search with transactions - Determine when to use transactions vs. stats - Report on transactions - Group events using fields - Group events using fields and time |
| Topic 3: Creating Tags and Event Types | 10% | - Describe event types and their uses - Create an event type - Create and use tags |
| Topic 4: Filtering and Formatting Results | 10% | - The fillnull command - Use the search and where commands to filter results - The eval command |
| Topic 5: Using the Common Information Model (CIM) Add-On | 10% | - Describe the Splunk CIM - Describe the use of the CIM Add-On |
| Topic 6: Creating and Using Macros | 10% | - Create and use a basic macro - Define arguments and variables for a macro - Describe macros - Add and use arguments with a macro |
| Topic 7: Using Transforming Commands for Visualizations | 5% | - Use the timechart command - Use the chart command |
| Topic 8: Creating Data Models | 10% | - Create a data model - Identify data model attributes - Describe the relationship between data models and pivot |
| Topic 9: Creating and Using Workflow Actions | 10% | - Describe the function of GET, POST, and Search workflow actions - Create a Search workflow action - Create a GET workflow action - Create a POST workflow action |
| Topic 10: Creating Field Aliases and Calculated Fields | 10% | - Describe, create, and use field aliases - Describe, create, and use calculated fields |
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NEW QUESTION # 18
Data model are composed of one or more of which of the following datasets? (select all that apply.)
Answer: A,B,D
Explanation:
Reference: https://docs.splunk.com/Documentation/Splunk/8.0.3/Knowledge/Aboutdatamodels 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. Data models can be composed of one or more of the following datasets:
Events datasets: These are the base datasets that represent raw events in Splunk. Events datasets can be filtered by constraints, such as search terms, sourcetypes, indexes, etc.
Search datasets: These are derived datasets that represent the results of a search on events or other datasets.
Search datasets can use any search command, such as stats, eval, rex, etc., to transform the data.
Transaction datasets: These are derived datasets that represent groups of events that are related by fields, time, or both. Transaction datasets can use the transaction command or event types with transactiontype=true to create transactions.
NEW QUESTION # 19
Why are tags useful in Splunk?
Answer: C
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 # 20
Which of the following knowledge objects represents the output of an eval expression?
Answer: A
Explanation:
Reference:
The eval command is used to create new fields or modify existing fields based on an expression2. The output of an eval expression is a calculated field, which is a field that you create based on the value of another field or fields2. You can use calculated fields to enrich your data with additional information or to transform your data into a more useful format2. Therefore, option B is correct, while options A, C and D are incorrect because they are not names of knowledge objects that represent the output of an eval expression.
NEW QUESTION # 21
Which of the following knowledge objects represents the output of an eval expression?
Answer: A
Explanation:
Reference:https://docs.splunk.com/Splexicon:Calculatedfield
The eval command is used to create new fields or modify existing fields based on an expression2. The output
of an eval expression is a calculated field, which is a field that you create based on the value of another field or
fields2. You can use calculated fields to enrich your data with additional information or to transform your data
into a more useful format2. Therefore, option B is correct, while options A, C and D are incorrect because they
are not names of knowledge objects that represent the output of an eval expression.
NEW QUESTION # 22
Which of the following data model are included In the Splunk Common Information Model (CIM) add-on?
(select all that apply)
Answer: B,C,D
Explanation:
Reference: https://docs.splunk.com/Documentation/CIM/4.15.0/User/Overview The Splunk Common Information Model (CIM) add-on is a collection of pre-built data models and knowledge objects that help you normalize your data from different sources and make it easier to analyze and report on it3. The CIM add-on includes several data models that cover various domains such as Alerts, Email, Database, Network Traffic, Web and more3. Therefore, options A, B and C are correct because they are names of some of the data models included in the CIM add-on. Option D is incorrect because User permissions is not a name of a data model in the CIM add-on.
NEW QUESTION # 23
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