Pass the ServiceNow CIS-Platform Analytics CIS-PA Questions and answers with CertsForce

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 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.

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.

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.

In ServiceNow Platform Analytics, thePrecisionsetting controls how numeric values arerounded and abbreviatedwhen displayed inScore widgets. When Precision is set to0, the platform displays values usingcompact notation(such askfor thousands orMfor millions) withno decimal places.

For a stored value of7423.3, Precision 0 causes the value to be rounded to the nearest thousand and displayed as7k. Platform Analytics does not display the full raw number unless compact notation is disabled or precision is increased. Option B (7000) and option D (7423) represent numeric rounding but not thecompact display formatused by score widgets. Option C is incorrect because Precision 0 explicitly removes decimals and applies abbreviation.

ServiceNow documentation confirms that score widgets useprecision-based compact formatting, making7kthe correct displayed value when Precision is set to 0.

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 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.

To track how long an incident remains assigned to a specific group, the correct Metric Definition type isField value duration. This type measures the amount of time a record spends with a particular value in a specified field, such as assignment_group.

State change metrics track transitions between states, not time spent in a field value. Script calculations are used only when duration cannot be calculated through standard field tracking. “Assignment group” is a field, not a metric type. ServiceNow documentation specifies that Field value duration metrics are designed for tracking time spent in a given field value, making option A the correct choice.

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.

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.