ServiceNow Certified Implementation Specialist - Platform Analytics CIS-PA Exam Dumps: Updated Questions & Answers (February 2026)

A Bucket Group is used in Platform Analytics to categorize numeric or time-based values into ranges. The Hour of day breakdown is a classic example of this usage, as it groups records into defined hourly ranges (for example, 00–01, 01–02, and so on).

Priority, Business Service, and Assignment Group are categorical fields that use direct field mappings and do not require bucket logic. Bucket Groups are specifically intended for non-categorical data such as time, age, duration, or numeric ranges. ServiceNow documentation explicitly identifies time-based breakdowns, such as hour of day or age ranges, as appropriate use cases for Bucket Groups. Therefore, option A is the correct answer.

By default, a newly created Platform Analytics indicator isVisible to Just Me, andVisible by All Rolesis set toFalse. This ensures that indicators are private to their creator until explicitly shared.

No role is required by default, and visibility must be intentionally expanded by updating the access control settings. This design supports governance and prevents incomplete or experimental indicators from being exposed prematurely. ServiceNow documentation confirms this default behavior, making option A the correct answer.

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.

Breakdown element securitydetermines which users are allowed to see specific breakdown elements (such as certain categories or values) when viewing analytics data. In Platform Analytics, this security is configured directly on theAutomated Breakdownrecord.

Automated Breakdowns include properties that allow administrators to defineelement-level access control, typically by specifyingrolesthat are required to view certain breakdown elements. This ensures sensitive analytics data is only visible to authorized users. The Breakdown Source defines how data is mapped and categorized but does not control visibility. Automated Indicators control score collection and aggregation, not breakdown element security. Manual Breakdowns are static and do not support dynamic element security in the same way.

ServiceNow documentation explicitly states that breakdown element security settings—such as restricting elements by role—are part of theAutomated Breakdown configuration, making option D the correct answer.

Ascripted Breakdown Mappingis required when the breakdown value cannot be obtained through adirect field mappingor simple reference relationship. Categorizing requests based onthe number of times they were updatedrequires calculating a value dynamically (for example, counting updates from the audit history), which is not stored as a single field on the record. Because this value must be derived programmatically, a scripted mapping is necessary.

Options B and C use existing fields (category, priority) that can be mapped directly without scripting. Option D usesage ranges, which are handled throughBucket Groupsand thepa_bucketstable, not scripted mappings. ServiceNow documentation clearly states that scripted mappings are intended forcalculated, derived, or indirect values, making option A the correct answer.

Analytics Centeris the workspace used to create and manageNext Experience DashboardsandData Visualizations. It provides a unified interface for building modern, interactive analytics experiences, including metric visualizations, time series, breakdown views, and dashboards.

Analytics Hub is primarily used forviewing and exploring existing analytics, not creating them. Reports Administration and Analytics Administration serve different purposes and do not support Next Experience dashboard creation. ServiceNow documentation explicitly identifies Analytics Center as the creation and management environment for Next Experience analytics content, making option D the correct answer.

In Responsive Canvas dashboards, when a Time Series widget contains multiple elements, theShow multiple elements asproperty controls how those elements are visualized. Setting this property toAggregatecombines the values of all returned elements into asingle trend line, which is exactly the desired outcome when viewing a combined trend for High and Critical priority incidents.

Applying an elements filter (option D) limits which elements are displayed but does not combine them into one trend. Setting the property toSeparate(option C) explicitly shows individual trend lines for each element. Manually adding elements (option B) still results in multiple distinct series unless aggregation is enabled. According to ServiceNow Platform Analytics documentation, aggregation is the correct method for consolidating multiple indicator elements into one unified visualization on a dashboard.

Fiscal Calendarsallow Platform Analytics to aggregate and visualize indicator data usingfiscal periodssuch as fiscal years, quarters, and accounting periods. This is essential for organizations that do not follow standard calendar years for reporting and performance measurement.

Gregorian calendars use standard date boundaries, while Business Calendars define working and non-working time for duration calculations. Timecard calendars are unrelated to analytics aggregation. ServiceNow documentation clearly states that fiscal period-based analysis is enabled through Fiscal Calendars, making optionBthe correct answer.

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.

In ServiceNow Platform Analytics, aBreakdown Sourceis automatically disabled when the number of generated breakdown elements exceeds themaximum element limitdefined in system properties (for example, properties controlling the maximum allowed breakdown elements during data collection). This safeguard exists to protect system performance and prevent excessive storage and processing during data collection jobs.

When this error occurs, therecommended and documented resolutionisnotto increase the system property arbitrarily. Increasing the global limit can negatively impact performance across all analytics workloads and is discouraged unless there is a strong architectural justification.

Instead, ServiceNow best practice is torefine the Breakdown Source conditions—for example, by adding filters, narrowing scope, or excluding unnecessary records—so that the number of returned elements fallsbelow the configured system threshold. Once the conditions are optimized, you can safely re-enableDC active, and the breakdown will participate in data collection successfully.

Simply re-enabling DC active without reducing elements will cause the breakdown to be disabled again, and deleting/recreating the source does not address the root cause. Therefore,option Dis the correct and fully supported resolution according to ServiceNow Platform Analytics documentation and best practices.