Latest Braindumps Splunk SPLK-3002 Book | Free SPLK-3002 Test Questions

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Splunk SPLK-3002 Exam is designed for IT professionals who want to validate their skills and knowledge in using Splunk IT Service Intelligence (ITSI) to manage IT services. Splunk IT Service Intelligence Certified Admin certification exam is a comprehensive assessment of an individual's ability to install, configure, and manage ITSI in a Splunk environment. SPLK-3002 exam is an online proctored test that consists of 60 multiple-choice and multiple-select questions. It has a time limit of 90 minutes, and the passing score is 70%.

Prerequisites for the Splunk SPLK-3002 Exam

Splunk IT Service Intelligence Certified Admin (ITI-CA) is the entry level certification for the Splunk IT Service Intelligence learning path. This certification validates a candidate's basic skills to use Splunk software to analyze data, monitor networks, and troubleshoot problems.

The ITI-CA certification is focused on real world skills and knowledge including:

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Splunk IT Service Intelligence Certified Admin Sample Questions (Q28-Q33):

NEW QUESTION # 28
Which of the following is a recommended best practice for service and glass table design?

Answer: D


NEW QUESTION # 29
To use Adaptive Threshholding, what is the minimum requirement for a set of KPI data?

Answer: D

Explanation:
To utilize Adaptive Thresholding in Splunk IT Service Intelligence (ITSI), the minimum requirement for a set of Key Performance Indicator (KPI) data is that it must be at least 7 days old. Adaptive Thresholding uses historical data to dynamically adjust thresholds based on observed patterns and trends. Having a minimum of 7 days worth of data allows the system to analyze a sufficient amount of information to identify normal ranges and variances in KPI behavior, thereby setting more accurate and contextually relevant thresholds. This requirement ensures that the adaptive thresholds are based on a meaningful data set that reflects the typical operational conditions of the monitored services.


NEW QUESTION # 30
When creating a custom deep dive, what color are services/KPIs in maintenance mode within the topology view?

Answer: B

Explanation:
When creating a custom deep dive, services or KPIs that are in maintenance mode are shown in gray color in the topology view. This indicates that they are not actively monitored and do not generate alerts or notable events. References: Deep Dives


NEW QUESTION # 31
After a notable event has been closed, how long will the meta data for that event remain in the KV Store by default?

Answer: A

Explanation:
By default, notable event metadata is archived after six months to keep the KV store from growing too large.
Reference: https://docs.splunk.com/Documentation/ITSI/4.10.2/EA/TrimNECollections


NEW QUESTION # 32
Which of the following is an advantage of using adaptive time thresholds?

Answer: D

Explanation:
Reference:
Adaptive thresholds are thresholds calculated by machine learning algorithms that dynamically adapt and change based on the KPI's observed behavior. Adaptive thresholds are useful for monitoring KPIs that have unpredictable or seasonal patterns that are difficult to capture with static thresholds. For example, you might use adaptive thresholds for a KPI that measures web traffic volume, which can vary depending on factors such as holidays, promotions, events, and so on. The advantage of using adaptive thresholds is:
A) Automatically update thresholds daily to manage dynamic changes to KPI values. This is true because adaptive thresholds use historical data from a training window to generate threshold values for each time block in a threshold template. Each night at midnight, ITSI recalculates adaptive threshold values for a KPI by organizing the data from the training window into distinct buckets and then analyzing each bucket separately. This way, the thresholds reflect the most recent changes in the KPI data and account for any anomalies or trends.
The other options are not advantages of using adaptive thresholds because:
B) Automatically adjust KPI calculation to manage dynamic event data. This is not true because adaptive thresholds do not affect the KPI calculation, which is based on the base search and the aggregation method. Adaptive thresholds only affect the threshold values that are used to determine the KPI severity level.
C) Automatically adjust aggregation policy grouping to manage escalating severity. This is not true because adaptive thresholds do not affect the aggregation policy, which is a set of rules that determines how to group notable events into episodes. Adaptive thresholds only affect the threshold values that are used to generate notable events based on KPI severity level.
D) Automatically adjust correlation search thresholds to adjust sensitivity over time. This is not true because adaptive thresholds do not affect the correlation search, which is a search that looks for relationships between data points and generates notable events. Adaptive thresholds only affect the threshold values that are used by KPIs, which can be used as inputs for correlation searches.


NEW QUESTION # 33
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