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| Section | Weight | Objectives |
|---|---|---|
| Creating and Using Field Aliases and Calculated Fields | 10% | - Manage field extractions and aliases - Create calculated fields with eval - Define and use field aliases |
| Transforming Commands and Visualizations | 15% | - Create and customize visualizations - Use transforming commands to structure data - Format results for presentation |
| Filtering and Formatting Results | 15% | - Use search and where commands - Use fillnull, eval, and other formatting commands - Sort, rename, and limit results |
| Creating Data Models | 10% | - Define data model objects and attributes - Understand data models and Pivot - Create and use data models |
| Using Macros | 10% | - Add and use arguments in macros - Create and reuse search macros - Manage macro permissions and sharing |
| Creating and Using Workflow Actions | 10% | - Use workflow actions to extend searches - Describe GET, POST, and Search workflow actions - Create and configure workflow actions |
| 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 |
| Correlating Events | 15% | - Compare transactions vs stats commands - Identify and use transactions - Group events by fields and time |
| Creating Tags and Event Types | 10% | - Use tags and event types in searches - Create and apply tags to fields or values - Define event types to categorize events |
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NEW QUESTION # 45
There are several ways to access the field extractor. Which option automatically identifies data type, source type, and sample event?
Answer: A
Explanation:
Explanation
There are several ways to access the field extractor. The option that automatically identifies data type, source type, and sample event is Fields sidebar > Extract New Field. The field extractor is a tool that helps you extract fields from your data using delimiters or regular expressions. The field extractor can generate a regex for you based on your selection of sample values or you can enter your own regex in the field extractor. The field extractor can be accessed by using various methods, such as:
Fields sidebar > Extract New Field: This is the easiest way to access the field extractor. The fields sidebar is a panel that shows all available fields for your data and their values. When you click on Extract New Field in the fields sidebar, Splunk will automatically identify the data type, source type, and sample event for your data based on your current search criteria. You can then use the field extractor to select sample values and generate a regex for your new field.
Event Actions > Extract Fields: This is another way to access the field extractor. Event actions are actions that you can perform on individual events in your search results, such as viewing event details, adding to report, adding to dashboard, etc. When you click on Extract Fields in the event actions menu, Splunk will use the current event as the sample event for your data and ask you to select the source type and data type for your data. You can then use the field extractor to select sample values and generate a regex for your new field.
Settings > Field Extractions > New Field Extraction: This is a more advanced way to access the field extractor. Settings is a menu that allows you to configure various aspects of Splunk, such as indexes, inputs, outputs, users, roles, apps, etc. When you click on New Field Extraction in the Settings menu, Splunk will ask you to enter all the details for your new field extraction manually, such as app context, name, source type, data type, sample event, regex, etc. You can then use the field extractor to verify or modify your regex for your new field.
NEW QUESTION # 46
Which tool uses data models to generate reports and dashboard panels without using SPL?
Answer: C
Explanation:
The correct answer is B. Pivot1.
In Splunk, Pivot is a tool that uses data models to generate reports and dashboard panels without the need for users to write or understand Splunk's Search Processing Language (SPL)1. Data models enable users of Pivot to create compelling reports and dashboards1. When a Pivot user designs a pivot report, they select the data model that represents the category of event data that they want to work with1. Then they select a dataset within that data model that represents the specific dataset on which they want to report1. This makes Pivot a powerful tool for users who need to create visualizations but do not have a deep understanding of SPL1.
NEW QUESTION # 47
Which of the following eval command functions is valid?
Answer: B
Explanation:
https://docs.splunk.com/Documentation/Splunk/latest/SearchReference/CommonEvalFunctions
NEW QUESTION # 48
Which of the following knowledge objects represents the output of an evalexpression?
Answer: D
Explanation:
Explanation/Reference: https://docs.splunk.com/Splexicon:Calculatedfield
NEW QUESTION # 49
Which command can include both an overand a byclause to divide results into sub-groupings?
Answer: B
Explanation:
Explanation/Reference: https://www.splunk.com/en_us/blog/tips-and-tricks/search-commands-stats-chart-and- timechart.html
NEW QUESTION # 50
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