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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Exploring Data Models | 10% | - Creating data models - Using pivot - Understanding data models - Using data model objects |
| Topic 2: Exploring Field Extractions | 10% | - Using the Field Extractor - Using calculated fields - Using field aliases - Creating custom fields |
| Topic 3: Exploring Statistical Commands | 4% | - Using appendpipe - Performing statistical analysis with stats function - Using eventstats - Using fieldsummary - Using count and list functions - Using streamstats |
| Topic 4: Exploring Dashboards and Forms | 15% | - Using tokens - Creating dashboards using Simple XML - Using event handlers - Using drilldowns - Using dynamic form inputs |
| Topic 5: Exploring Alerts | 4% | - Logging and indexing searchable alert events - Referencing alert actions - Using alert manager - Understanding alert actions |
| Topic 6: Exploring Lookups | 4% | - Using external lookups - Applying advanced lookup options - Using geospatial lookups - Including and excluding events based on lookup values - Using KV Store lookups - Understanding best practices for lookups |
| Topic 7: Exploring eval Command Functions | 4% | - Using comparison and conditional functions - Using makeresults command - Using conversion functions - Using statistical functions - Using informational functions - Using text functions |
| Topic 8: Exploring Search Optimization | 10% | - Using summary indexing - Using report acceleration - Using search optimization techniques - Using tsidx files |
| Topic 9: Exploring Splunk's Search Processing Language | 15% | - Using tags and event types - Using workflow actions - Using advanced search commands - Using search macros - Using transactions |
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NEW QUESTION # 63
Which of the following best describes the process for tokenizing event data?
Answer: D
Explanation:
The process for tokenizing event data in Splunk involves breaking the event data up by major breakers (which typically identify the boundaries of events) and further breaking it up by minor breakers (which segment the event data into fields). This hierarchical approach allows Splunk to efficiently parse and structure the data.
NEW QUESTION # 64
How can the inspect button be disabled on a dashboard panel?
Answer: B
Explanation:
To disable the inspect button on a dashboard panel in Splunk, you can set the link.inspect.visible attribute to 0 (Option B) in the panel's source code. This attribute controls the visibility of the inspect button, and setting it to 0 hides the button, preventing users from accessing the search inspector for that panel.
NEW QUESTION # 65
What arguments are required when using the spath command?
Answer: B
Explanation:
The spath command in Splunk requires the input and output path arguments. The input specifies the field or data source to parse, and the path defines the location of the data within a structured format like JSON or XML.
NEW QUESTION # 66
A report named "Linux logins" populates a summary index with the search string sourcetype=linux_secure| sitop src_ip user. Which of the following correctly searches against the summary index for this data?
Answer: A
Explanation:
When searching against summary data in Splunk, it's common to reference the name of the saved search or report that populated the summary index. The correct search syntax to retrieve data from the summary index populated by a report named "Linux logins" is index=summary search_name="Linux logins" | top src_ip user (Option B). This syntax uses the search_name field, which holds the name of the saved search or report that generated the summary data, allowing for precise retrieval of the intended summary data.
NEW QUESTION # 67
When enabled, what drilldown action is performed when a visualization is clicked in a dashboard?
Answer: D
Explanation:
Comprehensive and Detailed Step by Step Explanation:
When drilldown is enabled in a Splunk dashboard, clicking on a visualization triggers arefresh of the search results for the selected visualization. This allows users to interact with the data and refine the displayed results based on the clicked value.
Here's why this works:
* Drilldown Behavior: Drilldown actions are configured to dynamically update tokens or filters based on user interactions. When a user clicks on a chart, table, or other visualization, the underlying search query is updated to reflect the selected value.
* Contextual Updates: The refresh applies only to the selected visualization, ensuring that other panels in the dashboard remain unaffected unless explicitly configured otherwise.
Other options explained:
* Option A: Incorrect because visualizations are not automatically opened in a new window during drilldown.
* Option C: Incorrect because drilldown actions typically affect only the selected visualization, not all panels in the dashboard.
* Option D: Incorrect because a new search window is not opened unless explicitly configured in the drilldown settings.
Example:
<drilldown>
<set token="selected_value">$click.value$</set>
</drilldown>
In this example, clicking on a value updates theselected_valuetoken, which can be used to filter the visualization's search results.
References:
Splunk Documentation on Drilldowns:https://docs.splunk.com/Documentation/Splunk/latest/Viz
/DrilldownIntro
Splunk Documentation on Tokens:https://docs.splunk.com/Documentation/Splunk/latest/Viz
/UseTokenstoBuildDynamicInputs
NEW QUESTION # 68
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