CIS-PA Fragen & Antworten & CIS-PA Studienführer & CIS-PA Prüfungsvorbereitung

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ServiceNow CIS-PA Prüfungsplan:

Thema	Einzelheiten
Thema 1	Data Collection: This domain explains how Performance Analytics gathers and processes data, including collection flow, configuration properties, and troubleshooting collection issues.
Thema 2	Data Visualization: This section focuses on presenting data through widgets, interactive filters, appropriate visualizations, dashboards, and analyzing data using Analytics Hub and KPI Details.
Thema 3	Configure Indicators and Indicator Sources: This domain addresses creating and configuring indicators (performance metrics), including source conditions, fact tables, indicator types, properties, and aggregation scripts.

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ServiceNow Certified Implementation Specialist - Platform Analytics CIS-PA Prüfungsfragen mit Lösungen (Q38-Q43):

38. Frage
Which user should you run Data Collections as?

A. Maintenance account (maint)
B. Platform Analytics Admin
C. System Administrator
D. A dedicated Performance Analytics service account

Antwort: D

Begründung:
ServiceNow best practice recommends running Performance Analytics data collections using a dedicated service account specifically created for analytics processing. This ensures consistent permissions, predictable access to data, and improved auditability.
Running collections as individual admins can introduce permission inconsistencies if roles change. The maint account is intended for system upgrades and maintenance, not scheduled analytics jobs. A dedicated Performance Analytics service account minimizes operational risk and aligns with ServiceNow security and governance guidelines.
ServiceNow documentation emphasizes the importance of service accounts for background processing, making option C the correct and recommended choice.

39. Frage
When using aBucket Groupas a Breakdown Source, which is the required Breakdown SourceFacts table?

A. Bucket [pa_buckets]
B. The Indicator Facts table
C. Choice [sys_choice]
D. Bucket Group [pa_bucket_groups]

Antwort: A

Begründung:
When aBucket Groupis used as a Breakdown Source in Platform Analytics, the requiredFacts tableisBucket
[pa_buckets]. Bucket Groups define how numeric or duration values (such as age, time, or cost ranges) are grouped, but they do not store analytics facts themselves. The actual bucketed values generated during data collection are stored in thepa_bucketstable, which makes it the authoritative facts table for bucket-based breakdowns.
Thepa_bucket_groupstable only stores configuration metadata for bucket definitions. Thesys_choicetable is used exclusively for choice list values and is unrelated to bucket analytics. The Indicator Facts table stores indicator scores but does not contain bucket-level breakdown data. ServiceNow documentation explicitly states that any breakdown based on bucket groups must reference thepa_bucketstable to ensure accurate historical analysis and proper breakdown rendering. Therefore, option C is the only correct answer.

40. Frage
How can aBreakdownbe applied tomultiple Indicatorsbased ondifferent Facts tables?

A. Create a mapping script to define the relationship between the indicator facts tables and the breakdown source
B. Configure the indicators to use the same indicator source
C. Create a separate breakdown mapping for each indicator facts table
D. Create a separate breakdown record for each indicator facts table

Antwort: C

Begründung:
A single Breakdown can be reused across multiple indicators-even when those indicators are based on different facts tables-by creating aseparate Breakdown Mapping for each indicator facts table.
The Breakdown defineswhatis being analyzed, while the Breakdown Mapping defineshowthe indicator facts relate to the breakdown source. Because different facts tables may store data differently, each requires its own mapping configuration. A scripted mapping is only required when no direct relationship exists, not simply because facts tables differ. ServiceNow documentation clearly states that reuse across facts tables is achieved through multiple mappings, making option D the correct answer.

41. Frage
How many queries are performed against the database when aDaily Data Collection jobis executed?

A. One for each automated indicator
B. One for each indicator type
C. One for each indicator frequency
D. One for each indicator source

Antwort: D

Begründung:
During a Daily Data Collection job, Platform Analytics executesone database query per Indicator Source, not per indicator. Multiple indicators can reference the same indicator source, allowing the platform toreuse the result setand calculate multiple scores from a single query.
This design is a key performance optimization in Platform Analytics. Executing queries per indicator would significantly increase database load, especially in large implementations. ServiceNow documentation explicitly states that indicator sources are the unit of data retrieval during collection, making option B the correct and documented answer.

42. Frage
What is the default aggregation for the Metric tile in a Data Visualization?

A. AVERAGE
B. MIN
C. SUM
D. COUNT

Antwort: D

Begründung:
In Platform Analytics data visualizations, the Metric tile is designed to display a single summarized value. By default, the aggregation used for a Metric tile is COUNT. This means the tile displays the total number of records or scores returned by the data source unless the aggregation is explicitly changed by the user.
COUNT is the most commonly used aggregation because Metric tiles are often used to show key headline numbers such as total incidents, open requests, or completed tasks. Other aggregations like AVERAGE, MIN, or SUM are available options, but they must be manually selected during configuration. ServiceNow documentation confirms that COUNT is the default aggregation applied to Metric visualizations, making option A the correct answer.

43. Frage
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