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| Section | Weight | Objectives |
|---|---|---|
| Using Macros | 10% | - Create and reuse search macros - Manage macro permissions and sharing - Add and use arguments in macros |
| 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 |
| Filtering and Formatting Results | 15% | - Use search and where commands - Use fillnull, eval, and other formatting commands - Sort, rename, and limit results |
| Creating and Using Field Aliases and Calculated Fields | 10% | - Manage field extractions and aliases - Define and use field aliases - Create calculated fields with eval |
| Creating and Using Workflow Actions | 10% | - Create and configure workflow actions - Describe GET, POST, and Search workflow actions - Use workflow actions to extend searches |
| Creating Data Models | 10% | - Understand data models and Pivot - Define data model objects and attributes - Create and use data models |
| Using the Common Information Model (CIM) Add-On | 5% | - Normalize data using CIM knowledge objects - Use CIM to standardize data across sources - Describe Splunk CIM purpose and structure |
| Correlating Events | 15% | - Identify and use transactions - Group events by fields and time - Compare transactions vs stats commands |
| Transforming Commands and Visualizations | 15% | - Format results for presentation - Use transforming commands to structure data - Create and customize visualizations |
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NEW QUESTION # 83
Which of the following statements describe data model acceleration? (select all that apply)
Answer: B,D
NEW QUESTION # 84
Which group of users would most likely use pivots?
Answer: A
Explanation:
Reference: https://docs.splunk.com/Documentation/Splunk/8.0.3/Pivot/IntroductiontoPivot A pivot is a tool that allows you to create reports and dashboards using data models without writing any SPL commands2. You can use pivots to explore, filter, split and visualize your data using a graphical interface2. Pivots are designed for users who want to analyze and report on their data without having to learn the SPL syntax or the underlying structure of the data2. Therefore, option A is correct, while options B, C and D are incorrect because they are not the typical group of users who would use pivots.
NEW QUESTION # 85
Which of the following statements is true about the root dataset of a data model?
Answer: B
Explanation:
In Splunk, a data model's root dataset is the foundational element upon which the rest of the data model is built. The root dataset can be of various types, including search, transaction, or event-based datasets. One of the key features of the root dataset is that it automatically inherits the knowledge objects associated with its base search. These knowledge objects include field extractions, lookups, aliases, and calculated fields that are defined for the base search, ensuring that the root dataset has all necessary contextual information from the outset. This allows users to build upon this dataset with additional child datasets and objects without having to redefine the base search's knowledge objects.
NEW QUESTION # 86
Which of the following Statements about macros is true? (select all that apply)
Answer: A,D
Explanation:
A macro is a way to save a commonly used search string as a variable that you can reuse in other
searches1. When you create a macro, you can define arguments that are placeholders for values that you
specify at execution time1. The argument values are used to resolve the search string when the macro is
invoked, not when it is created1. Therefore, statements B and C are true, while statements A and D are false.
NEW QUESTION # 87
Data models are composed of one or more of which of the following datasets? (Choose all that apply.)
Answer: A,B,D
Explanation:
Explanation/Reference: https://docs.splunk.com/Documentation/Splunk/8.0.3/Knowledge/Aboutdatamodels
NEW QUESTION # 88
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