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Splunk Core Certified Power User Exam Sample Questions (Q140-Q145):

NEW QUESTION # 140
Which group of users would most likely use pivots?

A. Users
B. Administrators
C. Architects
D. Knowledge Managers

Answer: A

Explanation:
Reference:https://docs.splunk.com/Documentation/Splunk/8.0.3/Pivot/IntroductiontoPivot

NEW QUESTION # 141
Which of the following transforming commands can be used with transactions?

A. chart, timechart, stats, eventstats
B. chart, timechart, stats, diff
C. chart, timecha:t, stats, pivot
D. chart, timeehart, datamodel, pivot

Answer: A

Explanation:
Transforming commands are commands that change the format of the search results into a table or a chart. They can be used to perform statistical calculations, create visualizations, or manipulate data in various ways1.
Transactions are groups of events that share some common values and are related in some way. Transactions can be defined by using the transaction command or by creating a transaction type in the transactiontypes.conf file2.
Some transforming commands can be used with transactions to create tables or charts based on the transaction fields. These commands include:
chart: This command creates a table or a chart that shows the relationship between two or more fields. It can be used to aggregate values, count occurrences, or calculate statistics3.
timechart: This command creates a table or a chart that shows how a field changes over time. It can be used to plot trends, patterns, or outliers4.
stats: This command calculates summary statistics on the fields in the search results, such as count, sum, average, etc. It can be used to group and aggregate data by one or more fields5.
eventstats: This command calculates summary statistics on the fields in the search results, similar to stats, but it also adds the results to each event as new fields. It can be used to compare events with the overall statistics.
These commands can be applied to transactions by using the transaction fields as arguments. For example, if you have a transaction type named "login" that groups events based on the user field and has fields such as duration and eventcount, you can use the following commands with transactions:
| chart count by user : This command creates a table or a chart that shows how many transactions each user has.
| timechart span=1h avg(duration) by user : This command creates a table or a chart that shows the average duration of transactions for each user per hour.
| stats sum(eventcount) as total_events by user : This command creates a table that shows the total number of events for each user across all transactions.
| eventstats avg(duration) as avg_duration : This command adds a new field named avg_duration to each transaction that shows the average duration of all transactions.
The other options are not valid because they include commands that are not transforming commands or cannot be used with transactions. These commands are:
diff: This command compares two search results and shows the differences between them. It is not a transforming command and it does not work with transactions.
datamodel: This command retrieves data from a data model, which is a way to organize and categorize data in Splunk. It is not a transforming command and it does not work with transactions.
pivot: This command creates a pivot report, which is a way to analyze data from a data model using a graphical interface. It is not a transforming command and it does not work with transactions.
Explanation:
The correct answer is
Reference:
About transforming commands
About transactions
chart command overview
timechart command overview
stats command overview
[eventstats command overview]
[diff command overview]
[datamodel command overview]
[pivot command overview]

NEW QUESTION # 142
which of the following commands are used when creating visualizations(select all that apply.)

A. Geom
B. Choropleth
C. Geostats
D. iplocation

Answer: A,C,D

Explanation:
The following commands are used when creating visualizations: geom, geostats, and iplocation.
Visualizations are graphical representations of data that show trends, patterns, or comparisons. Visualizations
can have different types, such as charts, tables, maps, etc. Visualizations can be created by using various
commands that transform the data into a suitable format for the visualization type. Some of the commands that
are used when creating visualizations are:
geom: This command is used to create choropleth maps that show geographic regions with different
colors based on some metric. The geom command takes a KMZ file as an argument that defines the
geographic regions and their boundaries. The geom command also takes a field name as an argument
that specifies the metric to use for coloring the regions.
geostats: This command is used to create cluster maps that show groups of events with different sizes
and colors based on some metric. The geostats command takes a latitude and longitude field as
arguments that specify the location of the events. The geostats command also takes a statistical function
as an argument that specifies the metric to use for sizing and coloring the clusters.
iplocation: This command is used to create location-based visualizations that show events with different
attributes based on their IP addresses. The iplocation command takes an IP address field as an argument
and adds some additional fields to the events, such as Country, City, Latitude, Longitude, etc. The
iplocation command can be used with other commands such as geom or geostats to create maps based
on IP addresses.

NEW QUESTION # 143
Which of the following is true about a datamodel that has been accelerated?

A. They can still be used in the Pivot tool but only with the accelerate_pivot capability.
B. They can no longer be used in the Pivot tool.
C. They can be used with the |tstats command, but will only return that data which has been accelerated.
D. They can be used with Pivot, the | tstats command, or the | datamodel command.

Answer: D

Explanation:
A data model that has been accelerated can be used with Pivot, the | tstats command, or the | datamodel command (Option A). Acceleration pre-computes and stores results for quicker access, enhancing the performance of searches and analyses that utilize the data model, especially for large datasets. This makes accelerated data models highly efficient for use in various analytical tools and commands within Splunk.

NEW QUESTION # 144
Given the macro definition below, what should be entered into the Name and Arguments fileds to correctly configured the macro?

A. The macro name is sessiontracker(2) and the arguments are action, JESSIONID.
B. The macro name is sessiontracker(2) and the Arguments are $action$, $JESSIONID$.
C. The macro name is sessiontracker and the arguments are action, JESSIONID.
D. The macro name is sessiontracker and the arguments are $action$, $JESSIONID$.

Answer: A

Explanation:
Reference: https://docs.splunk.com/Documentation/Splunk/8.0.3/Knowledge/Definesearchmacros The macro definition below shows a macro that tracks user sessions based on two arguments: action and JSESSIONID.
sessiontracker(2)
The macro definition does the following:
It specifies the name of the macro as sessiontracker. This is the name that will be used to execute the macro in a search string.
It specifies the number of arguments for the macro as 2. This indicates that the macro takes two arguments when it is executed.
It specifies the code for the macro as index=main sourcetype=access_combined_wcookie action=$action$ JSESSIONID=$JSESSIONID$ | stats count by JSESSIONID. This is the search string that will be run when the macro is executed. The search string can contain any part of a search, such as search terms, commands, arguments, etc. The search string can also include variables for the arguments using dollar signs around them.
In this case, action and JSESSIONID are variables for the arguments that will be replaced by their values when the macro is executed.
Therefore, to correctly configure the macro, you should enter sessiontracker as the name and action, JSESSIONID as the arguments. Alternatively, you can use sessiontracker(2) as the name and leave the arguments blank.

NEW QUESTION # 145
......

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