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Splunk SPLK-1004 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Dashboards, Forms, and Visualizations20%- Dynamic dashboards and forms
  • 1. Tokens, inputs, dynamic drilldown, conditional rendering
- Advanced visualizations
  • 1. Custom visualizations, formatting, and layout
- Dashboard design best practices
Topic 2: Lookups and Data Enrichment15%- Lookup management
  • 1. Creating, editing, managing, and optimizing lookups
- Lookup types
  • 1. File-based, KV Store, external, geospatial lookups
- Subsearches and advanced lookup use cases
Topic 3: Knowledge Objects20%- Data models and Pivot
  • 1. Designing data models, using Pivot for analysis
- Macros and workflow actions
- Tags and event types
- Fields and field extractions
  • 1. Automatic, inline, and configured extractions; field aliases; calculated fields
Topic 4: Search Optimization and Performance15%- Writing efficient SPL
  • 1. Best practices, reducing search time, avoiding common mistakes
- Using commands for optimization
  • 1. tstats, highcharts, summary indexing
Topic 5: Alerts and Monitoring10%- Alert management and logging
- Alert configuration
  • 1. Trigger conditions, scheduling, actions, throttling
Topic 6: Advanced Searching and Reporting20%- Statistical commands
  • 1. stats, eventstats, streamstats, timechart
- Comparison and correlation
  • 1. Comparing values, joins, transactions, correlation searches
- eval command and functions
  • 1. Conversion, mathematical, string, date/time, conditional functions
- Result modification commands
  • 1. sort, rename, replace, fields, dedup, head, tail

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Splunk Core Certified Advanced Power User Sample Questions (Q73-Q78):

NEW QUESTION # 73
When possible, what is the best choice for summarizing data to improve search performance?

Answer: C


NEW QUESTION # 74
Repeating JSON data structures within one event will be extracted as what type of fields?

Answer: A

Explanation:
When Splunk encounters repeating JSON data structures in an event, they are extracted as multivalue fields.
These allow multiple values to be stored under a single field, which is common with arrays in JSON data.
When Splunk extracts repeating JSON data structures within a single event, it represents them asmultivalue fields. A multivalue field is a field that contains multiple values, which can be iterated over or expanded using commands likemvexpandorforeach.
Here's why this works:
* JSON Data Extraction: Splunk automatically parses JSON data into fields. If a JSON key has an array of values (e.g.,"products": ["productA", "productB", "productC"]), Splunk creates a multivalue field for that key.
* Multivalue Fields: These fields allow you to handle multiple values for the same key within a single event. For example, if the JSON keyproductscontains an array of product names, Splunk will store all the values in a single multivalue field namedproducts.
{
"event": "purchase",
"products": ["productA", "productB", "productC"]
}
References:
Splunk Documentation on JSON Data Extraction:https://docs.splunk.com/Documentation/Splunk/latest/Data
/ExtractfieldsfromJSON
Splunk Documentation on Multivalue Fields:https://docs.splunk.com/Documentation/Splunk/latest
/SearchReference/MultivalueEvalFunctions


NEW QUESTION # 75
What happens to panels with post-processing searches when their base search Is refreshed?

Answer: C

Explanation:
When the base search of a dashboard panel with post-processing searches is refreshed, the panels with these post-processing searches are refreshed automatically (Option C). Post-processing searches inherit the scope and results of the base search, and when the base search is updated or rerun, the post-processed results are recalculated to reflect the latest data.


NEW QUESTION # 76
Why use the tstats command?

Answer: B

Explanation:
The tstats command in Splunk is used to generate statistics on indexed fields, particularly from data models that have been accelerated (Option B). This command is highly efficient for summarizing large volumes of data because it operates on indexed-time summarizations rather than raw data, enabling faster search performance and reduced processing time. The tstats command is especially useful in scenarios where quick aggregation and analysis of indexed data are required, making it a powerful tool for exploring and reporting on data model information. While tstats can be seen as an alternative to some uses of the summary command (Option A), its primary utility is in its ability to leverage data model accelerations and indexed field statistics, rather than creating or referring to summary indexes. It does not specifically generate statistics on search-time fields (Option D) or create an accelerated data model (Option C), but rather it queries against existing accelerated data models.


NEW QUESTION # 77
Assuming a standard time zone across the environment, what syntax will always return ewnts from between
2:00am and 5:00am?

Answer: C

Explanation:
To always return events from between 2:00 AM and 5:00 AM, assuming a standard time zone across the environment, the correct Splunk search syntax is earliest=-2h@h AND latest=-5h@h (Option B). This syntax uses relative time modifiers to specify a range starting 2 hours ago from the current hour (-2h@h) and ending
5 hours ago from the current hour (-5h@h), effectively capturing the desired time window.


NEW QUESTION # 78
......

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