CIS-PA Certified Implementation Specialist - Platform Analytics Questions and Answers

AnAutomated Indicatorin Platform Analytics is defined as aseries of measurements collected over timethat represent the performance of a process. These measurements are stored astime series data, allowing organizations to analyze trends, patterns, and historical performance. Automated indicators rely onindicator sourcesandscheduled data collection jobsto collect data at defined intervals, such as daily or hourly.

Option B describes asnapshot report, which represents data at a single point in time and does not support trending. Option C refers tobreakdowns, which categorize indicator scores for deeper analysis but do not define the indicator itself. Option D describes thedata collection job, which is a mechanism used by automated indicators but not the indicator definition. ServiceNow documentation explicitly states that indicators represent performance over time, making option A the correct and most complete description of an Automated Indicator.

Theanalytics_filter_adminrole is responsible forgoverning dashboard filterswithin Analytics Center. Users with this role cancreate, edit, delete, and manage filters, as well as add filters to thefilter libraryfor reuse across dashboards.

This role does not control visualization design, breakdown security, or data validation. Its purpose is to ensure consistent and controlled use of filters across analytics experiences. ServiceNow documentation explicitly associates this role with filter administration, making option B the correct answer.

During data collection, Platform Analytics first applies theIndicator Source conditionsto retrieve the base dataset. Once the source data is identified, the system then evaluates theAdditional conditionsdefined on the Indicator itself.

This separation allows indicator-specific filtering without duplicating logic in the indicator source, supporting reuse and performance optimization. Additional conditions do not run in parallel with source conditions and are not evaluated at visualization time. ServiceNow documentation explicitly explains that Indicator conditions refine the datasetafterthe source query executes, making option D the correct answer.

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.

In ServiceNow Performance Analytics,Indicator SourcesandIndicatorsare distinct objects with different responsibilities, and understanding their behavior is essential for correct architecture and deployment.

Option A is correct.

Indicator Sources definehowandwhen raw data is queried, but they can be reused by multiple data collection jobs. Even if an Indicator Source is configured with aMonthly frequency, it can still be executed by aDaily data collection job. The job frequency controls execution timing, not the source frequency itself. This reuse is a documented performance optimization in Platform Analytics.

Option C is correct.

TheIndicator frequency is independent of the Indicator Source frequency. For example, an Indicator Source may collect daily raw data, while the Indicator aggregates and stores scores weekly or monthly. This separation allows flexible aggregation strategies and is explicitly supported by Platform Analytics design.

Option B is incorrectbecause Breakdowns require aBreakdown Mapping, but they are not inherently tied only to Automated Indicators, nor is this statement describing object behavior accurately in isolation.

Option D is incorrectbecause Breakdowns can be assigned to an Indicatorbefore or after data collection; they are applied when the next collection runs.

When a predefined filter condition is selected during data source configuration, Platform Analytics applies the filter immediately and displays it in the Conditions section, where it can be reviewed, modified, or extended. This allows administrators to start with a standard filter and refine it to meet specific analytics requirements.

The filter is not automatically saved for future use, nor does it automatically select the data source without user confirmation. ServiceNow documentation clarifies that predefined filters act as starting templates, not locked or persistent filters. Administrators retain full control to adjust conditions before saving the indicator or data source. Therefore, option D accurately describes the behavior.

TheShow real-time scoreoption is available only fornon-scripted Automated Indicators. These indicators are based on standard indicator sources and conditions that can be safely recalculated on demand without scripting complexity.

Scripted automated indicators and formula indicators depend on stored historical values and custom logic, which cannot be reliably recalculated in real time. Manual indicators rely on user-entered values and also do not support real-time calculation. ServiceNow documentation explicitly limits real-time scoring to non-scripted automated indicators to preserve performance and data integrity. Therefore, option D is the correct answer.

User Experience Analyticsis the application designed to analyzeuser behavior, including new versus returning users, session frequency, navigation paths, page views, and interaction patterns across the ServiceNow platform. It provides insights into how users engage with the platform and helps organizations optimize usability, adoption, and performance.

Responsive Dashboards and Next Experience Dashboards are visualization and UI frameworks, not behavioral analytics tools. Platform Analytics Workspace focuses on KPI monitoring and process performance, not clickstream or navigation behavior. ServiceNow documentation clearly positions User Experience Analytics as the solution for understanding how users interact with the platform, making option D the correct answer.

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.

In Platform Analytics, aTargetdefines the desired performance level for an indicator. TheReview Dateproperty specifies therecommended date to evaluate progresstoward that target. This date is used for governance and performance review purposes, helping stakeholders determine when to assess whether the indicator is trending appropriately toward its goal.

TheBaseline Datemarks the starting point for measurement, while theEnd Datedefines when the target expires or is no longer valid. TheImprovement Dateindicates when improvement efforts begin, not when performance should be evaluated. ServiceNow documentation clearly identifies the Review Date as the point in time when the target’s effectiveness and achievement should be assessed, making option D the correct answer.

When creating a breakdown based on theage of a task, the correctFacts tablefor the Breakdown Source isBucket [pa_buckets]. In Platform Analytics, age-based breakdowns (such as 0–5 days, 6–10 days, etc.) are not derived directly from the Task table. Instead, they usebucketed data, which is generated bybucket groupsduring data collection.

Thepa_bucketstable stores the calculated bucket values for records at collection time, making it the authoritative facts table for age, duration, and numeric range breakdowns. Bucket Groups define how values are grouped, while the Bucket table stores the actual bucket assignments used in analytics. The Task table itself cannot be used as the facts table for age breakdowns because Platform Analytics requires pre-aggregated, time-aware bucket data to ensure historical accuracy. The Choice table is only used for choice list values and is unrelated to numeric or age-based breakdowns. ServiceNow documentation clearly states that bucket-based breakdowns must reference thepa_bucketstable to function correctly and produce accurate time series analytics.

Platform Analytics helps reduce IT spending by enablingcost visibility, trend analysis, and optimization insights. Breaking downincident resolution costsallows organizations to identify high-cost incident categories, inefficient processes, or teams with unusually long resolution times. By correlating cost data with performance indicators, leaders can make data-driven decisions to streamline workflows, reduce rework, and optimize resource allocation.

User satisfaction surveys (option A) provide qualitative feedback but do not directly measure or reduce costs. Importing asset cost reports (option B) is a reporting or data integration activity, not an analytics-driven optimization approach. Automating password resets (option D) is an operational improvement but does not directly leverage Platform Analytics capabilities. ServiceNow documentation emphasizes that Platform Analytics supportsstrategic objectivessuch as cost reduction by revealing inefficiencies through indicators, breakdowns, and historical trend analysis—making option C the correct answer.

ABreakdown Sourcedefines how data isclassified into distinct breakdown elementsfor analysis. It identifies the table and field (or script) used to generate the unique values—such as categories, priorities, assignment groups, or buckets—that segment indicator scores.

Default element filters are configured on the Breakdown, not the Breakdown Source. Indicators are linked to Breakdowns through Breakdown Mappings, not selected at the source level. While bucket-based sources support non-categorical data, their core purpose remains identifying unique breakdown elements. ServiceNow documentation emphasizes that the Breakdown Source is responsible for definingwhere breakdown values come from and how they are identified, making option C the correct answer.

Formula Indicators in Platform Analytics arepre-calculated during data collectionand their results arestoredin the Indicator Facts table, just like automated indicators. They are not calculated in real time when a dashboard is viewed. Instead, they use the previously collected scores of their component indicators to compute a derived value at collection time.

This design ensures consistent historical analysis, predictable performance, and accurate trending. Real-time calculation would undermine historical integrity and dashboard performance, which is why ServiceNow explicitly avoids it for formula indicators. The stored results can then be reused across dashboards and reports without recalculation. ServiceNow documentation clearly states that formula indicators behave like other indicators in that they arepersisted for future analysis, making option C correct.

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.