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ServiceNow CIS-PA Exam Syllabus Topics:

TopicDetails
Topic 1
  • Configure Breakdowns and Breakdown Sources: This section covers setting up breakdowns to analyze indicators across different dimensions, including breakdown mappings, matrices, exclusions, scripted mappings, and bucket groups.
Topic 2
  • Architecture and Deployment: This domain covers the foundational components of the Performance Analytics solution and the proper deployment sequence in ServiceNow environments.
Topic 3
  • Data Collection: This domain explains how Performance Analytics gathers and processes data, including collection flow, configuration properties, and troubleshooting collection issues.
Topic 4
  • Administration and Solutions: This domain covers administrative tasks using the Admin Console and accelerating deployment with pre-built Content Packs.
Topic 5
  • Data Visualization: This section focuses on presenting data through widgets, interactive filters, appropriate visualizations, dashboards, and analyzing data using Analytics Hub and KPI Details.

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ServiceNow Certified Implementation Specialist - Platform Analytics Sample Questions (Q12-Q17):

NEW QUESTION # 12
Which definition best describes theKPI Detailsapplication?

Answer: C

Explanation:
TheKPI Detailsapplication provides anexploratory, in-depth view of individual indicators. It allows users to analyze trends, targets, forecasts, breakdowns, and historical performance beyond what is shown in high- level dashboards.
KPI Details is not a content pack and does not consist of predefined reports. While Analytics Hub displays summary KPI information, KPI Details is a dedicated application for deeper investigation and performance review. ServiceNow documentation clearly describes KPI Details as a drill-down analysis tool, making option B the correct answer.


NEW QUESTION # 13
Which configuration confirms that anAutomated Breakdownis using aBucket Group?

Answer: A

Explanation:
An Automated Breakdown is confirmed to be using aBucket Groupwhen theFacts table of the Breakdown Sourceis set toBucket [pa_buckets]. Bucket Groups define how numeric or duration values are grouped, but the actual bucketed analytics data is stored in thepa_bucketstable during data collection.
The Breakdown Source is responsible for defining where the breakdown facts originate. If its Facts table is pa_buckets, this indicates that the breakdown is based on bucketed values generated by a Bucket Group. The Breakdown record itself does not define the facts table, and default element filters or related list conditions do not establish the use of bucket data.
ServiceNow Platform Analytics documentation clearly states that all bucket-based breakdowns must reference pa_bucketsat the Breakdown Source level, making option C the correct and definitive answer.


NEW QUESTION # 14
How manySQL queriesare executed during a30-day historical collectionif all10 indicatorsin the historical collection share thesame daily indicator source?

Answer: D

Explanation:
Platform Analytics optimizes historical data collection by executingone query per indicator source per day, regardless of how many indicators reference that source. If 10 indicators share the same daily indicator source, the system executesonly one SQL query per day, not one per indicator.
Over a 30-day historical collection period, this results in30 SQL queries total. This optimization significantly reduces database load and improves performance. ServiceNow documentation explicitly highlights this behavior as a best-practice advantage of reusing indicator sources. Therefore, option C is the correct and documented answer.


NEW QUESTION # 15
Which Indicator should beexcluded from a Historic Data Collectionbecause its scores cannot be accurately collected?

Answer: B

Explanation:
Historic Data Collection is designed to accurately reconstructpast indicator scoresbased on historical records. Indicators that rely oncalculated age values, such assummed age of open problems, cannot be accurately reconstructed because age is atime-relative valuethat depends on the exact moment of calculation.
Count-based indicators (options A, B, and D) can be recalculated historically by evaluating record states at specific points in time. However, summing age values requires knowing the precise age of each record at each historical interval, which is not reliably reproducible. ServiceNow documentation explicitly warns against using historic data collection forage-based and duration-sum indicators, making option C the correct exclusion.


NEW QUESTION # 16
What is the purpose of using aBucket Group?

Answer: C

Explanation:
ABucket Groupin Platform Analytics is used togroup large sets of numeric or time-based values into a smaller, more meaningful number of ranges. Common examples include grouping ages into ranges (0-5 days, 6-10 days), durations into bands, or hours of the day into segments. This simplifies analysis and improves dashboard readability by reducing excessive breakdown elements.
Bucket Groups do not log incidents, manage roles, or control integrations. Instead, they support analytics by enabling structured classification of non-categorical data. ServiceNow documentation clearly positions Bucket Groups as a mechanism for transforming raw numeric or duration data into consumable breakdowns, making option B the correct answer.


NEW QUESTION # 17
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