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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Using the Common Information Model (CIM) Add-On | 10% | - Describe the use of the CIM Add-On - Describe the Splunk CIM |
| Topic 2: Creating and Using Workflow Actions | 10% | - Create a Search workflow action - Describe the function of GET, POST, and Search workflow actions - Create a POST workflow action - Create a GET workflow action |
| Topic 3: Creating and Using Macros | 10% | - Add and use arguments with a macro - Define arguments and variables for a macro - Describe macros - Create and use a basic macro |
| Topic 4: Using Transforming Commands for Visualizations | 5% | - Use the chart command - Use the timechart command |
| Topic 5: Creating Data Models | 10% | - Describe the relationship between data models and pivot - Create a data model - Identify data model attributes |
| Topic 6: Filtering and Formatting Results | 10% | - The fillnull command - Use the search and where commands to filter results - The eval command |
| Topic 7: Creating and Managing Fields | 10% | - Perform delimiter field extractions using the FX - Perform regex field extractions using the Field Extractor (FX) |
| Topic 8: Creating Tags and Event Types | 10% | - Create and use tags - Describe event types and their uses - Create an event type |
| Topic 9: Creating Field Aliases and Calculated Fields | 10% | - Describe, create, and use calculated fields - Describe, create, and use field aliases |
| Topic 10: Correlating Events | 15% | - Identify transactions - Group events using fields and time - Search with transactions - Group events using fields - Report on transactions - Determine when to use transactions vs. stats |
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NEW QUESTION # 116
Data model are composed of one or more of which of the following datasets? (select all that apply.)
Answer: A,C,D
Explanation:
Reference:
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 # 117
To create a tag, which of the following conditions must be met by the user?
Answer: B
Explanation:
To create a tag, the user must have the tag capability associated with their user role. The tag capability allows the user to create, edit, and delete tags. The user does not need to identify a field:value pair, have the Power role, or be able to edit the sourcetype the tag applies to.
Reference
See Define and manage tags in Settings and [About capabilities] in the Splunk Documentation.
NEW QUESTION # 118
In what order arc the following knowledge objects/configurations applied?
Answer: D
Explanation:
Reference: https://docs.splunk.com/Documentation/Splunk/8.0.3/Knowledge/WhatisSplunkknowledge Knowledge objects are entities that you create to add knowledge to your data and make it easier to search and analyze2. Some examples of knowledge objects are field extractions, field aliases and lookups2. Field extractions are methods that extract fields from your raw data using various techniques such as regular expressions, delimiters or key-value pairs2. Field aliases are ways to assign alternative names to existing fields without changing the original field names or values2. Lookups are ways to enrich your data with additional information from external sources such as CSV files or databases2. The order in which these knowledge objects/configurations are applied is as follows: field extractions, field aliases and then lookups2. This means that Splunk first extracts fields from your raw data, then applies any aliases to the extracted fields and then performs any lookups on the aliased fields2. Therefore, option B is correct, while options A, C and D are incorrect.
NEW QUESTION # 119
When adding a new field based on an eval expression in a data model, which option determines the field name that will appear to the user in Pivot?
Answer: D
Explanation:
When an eval expression field is added to a data model, the Display Name determines how that field is presented to users in Pivot.
Extract: "The display name is the name that appears for the field in Pivot."
NEW QUESTION # 120
A field alias has been created based on an original field. A search without any transforming commands is then executed in Smart Mode. Which field name appears in the results?
Answer: D
NEW QUESTION # 121
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