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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Collection | 10% | - Data collection process flow - Fine-tuning and troubleshooting collection jobs - Collection properties configuration |
| Topic 2: Configure Breakdowns and Breakdown Sources | 25% | - Breakdown sources configuration - Scripted breakdown mapping - Breakdown matrix and exclusions - Bucket groups configuration - Breakdown mappings |
| Topic 3: Administration and Advanced Implementation Solutions | 5% | - Spotlight configuration and usage - Advanced data collection scenarios - Content packs deployment |
| Topic 4: Configure Indicators and Indicator Sources | 25% | - Aggregation scripts creation - Indicator types and differences - Source conditions and facts tables configuration - Indicator configuration properties |
| Topic 5: Data Visualization and Dashboards | 25% | - Unified filters and interactions - KPI Details analysis and usage - Performance optimization and access control - Visualization types and selection - Dashboard creation and management |
| Topic 6: Architecture and Deployment | 10% | - Platform Analytics solution components - Common use cases - Personas and stakeholders - Deployment tasks and sequence |
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NEW QUESTION # 55
What configuration setting should be used to run aHistorical Collection Job?
Answer: C
Explanation:
AHistorical Collection Jobis designed to collect past data for a defined historical period and is typically executedone timeoron demand. Unlike scheduled collection jobs (daily, weekly, or monthly), historical jobs are not intended to run repeatedly.
ServiceNow documentation specifies that historical collections are initiated manually to backfill data for indicators that were created after records already existed. Running them on a recurring schedule could lead to duplicated or incorrect data. Therefore, the correct configuration isOnce or On Demand, making option A the correct answer.
NEW QUESTION # 56
How many queries are performed against the database when aDaily Data Collection jobis executed?
Answer: C
Explanation:
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.
NEW QUESTION # 57
What is an example of how Platform Analytics can help achieve the goal of reducing IT spending by 10%?
Answer: C
Explanation:
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.
NEW QUESTION # 58
When areAdditional conditionsof an Indicator evaluated duringData Collection?
Answer: B
Explanation:
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.
NEW QUESTION # 59
What determines thecolor of the scorein aScore widget?
Answer: D
Explanation:
In ServiceNow Platform Analytics, thecolor of the score displayed in a Score widgetis determined by the Indicator's relationship to its targetin combination with theDirection setting(Maximize or Minimize) of the Indicator. This behavior is part of the KPI evaluation logic and is consistent across dashboards and KPI Details.
When an indicator has a defined target, Platform Analytics compares thecurrent scoreagainst that target.
Based on whether the indicator is configured tomaximize(higher is better) orminimize(lower is better), the platform automatically assigns a visual status-such as green (on track), yellow (warning), or red (off track).
This status directly controls thecolor of the score valueshown in the widget.
Chart colors, field styles, or widget-specific settings donotinfluence the score color. Those options may affect line charts or visual styling, but not KPI status coloring. ServiceNow documentation clearly states that KPI status and score coloring are driven bytarget evaluation logic, makingoption Athe correct and verified answer.
NEW QUESTION # 60
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