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| Section | Objectives |
|---|---|
| Topic 1: Indicator Configuration | - Indicator types and setup
|
| Topic 2: Performance Analytics Fundamentals | - Key concepts of Performance Analytics
|
| Topic 3: Data Management and Administration | - Data collection jobs
|
| Topic 4: Breakdowns and Filtering | - Breakdown structure
|
| Topic 5: Widgets and Dashboards | - Visualization tools
|
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NEW QUESTION # 83
Which of the following scenarios require the use of a scripted Breakdown Mapping? (Choose two.)
Answer: A,C
Explanation:
The correct answers are B and D, because both scenarios require deriving values from Date/Time fields rather than directly grouping values already stored in suitable fields.
A scripted Breakdown Mapping is appropriate when the required categorization cannot be achieved through a straightforward field mapping.
Option B - Correct: Categorizing Tasks by the time elapsed since their last update requires calculating the difference between the task ' s sys_updated_on timestamp and the relevant collection-period date. The calculated duration can then be assigned to a bucket group containing age ranges. ServiceNow documents this approach through its Incident.Age.Days scripted breakdown example.
Option D - Correct: Categorizing Tasks by their creation hour requires extracting the hour component from sys_created_on. A script can transform the Date/Time value into an integer representing the appropriate hour, allowing records to be grouped into hourly buckets.
Option A - Incorrect: ServiceNow already maintains the number of record updates in sys_mod_count. This numeric field can be mapped directly into bucket ranges without requiring a script.
Option C - Incorrect: Incident Priority is an existing field that can be mapped directly to corresponding breakdown elements.
ServiceNow recommends using straightforward field mappings wherever possible, reserving scripts for calculated or transformed values.
Therefore, B and D are the correct selections.
ServiceNow+3
References: ServiceNow Performance Analytics - Scripting in Performance Analytics; Example: Script Mapping; Bucket Groups for Breakdown Sources; Breakdown Mapping Configuration; Task System Fields.
NEW QUESTION # 84
Select the role which can create new Interactive Filters.
Answer: C
Explanation:
The correct answer is C. report_admin, because this role is specifically associated with creating and administering Core UI Interactive Filters in ServiceNow.
Interactive Filters enable users to dynamically filter multiple report widgets on a dashboard without modifying the underlying report definitions.
For example, a dashboard may contain reports displaying incident counts, priorities, and assignment group performance. An interactive filter can allow users to select a particular assignment group and dynamically restrict the displayed report data.
ServiceNow supports several Core UI interactive filter types, including choice list, reference, date, Boolean, group, and cascading filters.
The report_admin role provides administrative permissions for Core UI reporting functionality, including interactive filter creation.
The pa_admin role primarily governs Performance Analytics administration, including indicators, breakdowns, and data collection. The pa_power_user role provides analytics authoring capabilities but is not the designated role for creating Core UI interactive filters.
Important release distinction: Beginning with the Australia release, ServiceNow explicitly restricts creation and editing of Core UI interactive filters to users with report_admin. Some earlier procedures also specify hp_publisher_admin as a required role.
In the newer Platform Analytics experience, creating filters through Filter Designer instead uses the analytics_filter_admin role or higher.
Among the listed options, report_admin is therefore the correct selection.
ServiceNow+3
References: ServiceNow - Interactive Filters; Creating Interactive Filters; Core UI Choice List Filters; Platform Analytics Roles; Report Administration.
NEW QUESTION # 85
Select the syntactically INCORRECT formula, assuming that all Indicator names are valid.
Answer: B
Explanation:
The correct answer is A, because it incorrectly uses double parentheses (( )) to reference Performance Analytics indicators.
ServiceNow Formula Indicators use specific reference delimiters to identify contributing indicators within JavaScript expressions.
The two primary formats are:
* [[Indicator Name]]: Retrieves an indicator score and permits applicable breakdowns to influence that score.
* {{Indicator Name}}: Retrieves an indicator score while preventing breakdowns applied to the Formula Indicator from affecting that component.
Option A incorrectly places the indicator names inside double parentheses, which JavaScript interprets as expression grouping rather than ServiceNow indicator references.
The corrected formula is:
([[Number of new critical incidents]] /
[[Number of new incidents]]) * 100
Option B uses supported indicator references and valid arithmetic operators to calculate a percentage difference relative to a reference value.
Option C uses a JavaScript conditional statement. Although its else expression would be clearer inside braces, the expression-statement syntax is valid after ServiceNow resolves the indicator reference.
Option D correctly combines square-bracket and curly-bracket references to calculate a breakdown ' s percentage contribution to the overall score.
ServiceNow recommends inserting indicator references through Browse for an indicator to ensure that the generated syntax is valid.
Therefore, A is the only option with an incorrect indicator-reference format.
ServiceNow+2
References: ServiceNow Performance Analytics - Create a Formula Indicator; Formula Indicator Syntax; JavaScript Expressions; Prevent a Contributing Indicator from Following Breakdowns; Formula Calculation Methods.
NEW QUESTION # 86
Which Indicator should you exclude from a Historic Data Collection because its scores cannot be accurately collected?
Answer: A
Explanation:
The correct answer is B. Number of open problems not updated in last 90 days, because this indicator depends on historical inactivity conditions that cannot be reliably reconstructed from current record values.
Historical data collection attempts to calculate indicator scores for previous reporting periods using information that remains available in the instance.
However, some indicators depend on time-sensitive conditions whose historical values are not preserved in the current operational record.
The indicator Number of open problems not updated in last 90 days evaluates whether a problem has remained unchanged during the preceding 90-day period.
Consider a problem last updated on October 15. A historical collection executed in November cannot reliably determine its last-update status for an earlier date if intervening updates have overwritten the prior sys_updated_on value.
As a result, historical collection may generate misleading scores.
Option A measures incidents resolved within a specified time condition and can potentially use retained resolution and SLA data.
Option C counts newly created requests, for which creation timestamps provide suitable historical information.
Option D measures problem age. Age calculations can be derived from creation dates and the applicable collection date when the relevant record population can be reconstructed.
ServiceNow specifically advises against historical collection for indicators measuring records not updated within a relative time window.
Instead, these indicators should be included in regular daily collection jobs to preserve accurate point-in-time measurements.
Knowledge Portal+2
References: ServiceNow Performance Analytics - Historical Data Collection; Historic Data Collection Limitations; Problem Management Indicators; Indicator Source Conditions; Data Collection Best Practices; ServiceNow Certification Exam Blueprint.
NEW QUESTION # 87
When using Text Analytics in Performance Analytics, what fields are analyzed?
Answer: C
Explanation:
The correct answer is C. Configured String fields from Indicator sources that have scores collected, because Text Analytics examines specifically configured textual information associated with Performance Analytics indicators.
Text Analytics enables organizations to extract meaningful information from unstructured text recorded in ServiceNow.
For example, administrators can analyze incident short descriptions to identify frequently occurring technical issues, recurring keywords, and emerging service problems.
The configuration process includes several stages.
First, an administrator selects an Indicator Source containing the relevant operational records.
Next, the administrator identifies the String fields to be analyzed. Common examples include Short description and other descriptive String fields.
ServiceNow does not support selecting arbitrary Journal fields, dot-walked fields, Translated Text fields, or fields with unsupported data types for this configuration.
The administrator then associates the Text Analytics configuration with the relevant indicators.
Finally, a data collection job runs to collect the required information and build the text indexes.
The resulting data can be displayed through Text Analytics widgets, including word clouds that illustrate frequently occurring terms.
The application does not automatically analyze every String field throughout the instance, nor is there a general restriction limiting analyzed strings to fewer than 100 characters.
Therefore, option C accurately describes the scope of Text Analytics processing.
References: ServiceNow Performance Analytics - Set Up Text Analytics; Text Index Configuration; Indicator Sources; Fields to Analyze; Collect Initial Text Analytics Data; Word Cloud Widgets.
NEW QUESTION # 88
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