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| Section | Weight | Objectives |
|---|---|---|
| Architecture and Deployment | 10% | - Deployment tasks and sequence - Common use cases - Platform Analytics solution components - Personas and stakeholders |
| Data Visualization and Dashboards | 25% | - Performance optimization and access control - Unified filters and interactions - Dashboard creation and management - KPI Details analysis and usage - Visualization types and selection |
| Data Collection | 10% | - Collection properties configuration - Fine-tuning and troubleshooting collection jobs - Data collection process flow |
| Administration and Advanced Implementation Solutions | 5% | - Spotlight configuration and usage - Content packs deployment - Advanced data collection scenarios |
| Configure Breakdowns and Breakdown Sources | 25% | - Bucket groups configuration - Breakdown sources configuration - Scripted breakdown mapping - Breakdown matrix and exclusions - Breakdown mappings |
| Configure Indicators and Indicator Sources | 25% | - Aggregation scripts creation - Indicator types and differences - Indicator configuration properties - Source conditions and facts tables configuration |
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NEW QUESTION # 33
What specifies thebase table and fieldused to uniquely identify elements in aBreakdown Source?
Answer: D
Explanation:
A Breakdown Source relies on theFacts tableand aunique identifier field (typically the Sys ID)to define how breakdown elements are generated and linked to indicator scores. The Facts table specifies where the breakdown data originates, while the Sys ID field uniquely identifies each breakdown element.
Related list conditions and labels do not define uniqueness. Indicator configuration and targets are unrelated to breakdown structure. Manual indicators and scoresheets are not involved in breakdown sourcing.
ServiceNow documentation clearly states that the Facts table and unique identifier are foundational to Breakdown Source configuration, making option B the correct answer.
NEW QUESTION # 34
Which configuration confirms that anAutomated Breakdownis using aBucket Group?
Answer: B
Explanation:
An Automated Breakdown is confirmed to be using aBucket Groupwhen theFacts table of the Breakdown Sourceis set toBucket [pa_buckets]. Bucket Groups define how numeric or duration values are grouped, but the actual bucketed analytics data is stored in thepa_bucketstable during data collection.
The Breakdown Source is responsible for defining where the breakdown facts originate. If its Facts table is pa_buckets, this indicates that the breakdown is based on bucketed values generated by a Bucket Group. The Breakdown record itself does not define the facts table, and default element filters or related list conditions do not establish the use of bucket data.
ServiceNow Platform Analytics documentation clearly states that all bucket-based breakdowns must reference pa_bucketsat the Breakdown Source level, making option C the correct and definitive answer.
NEW QUESTION # 35
Which scenarios require the use of ascripted Breakdown Mapping?
Answer: D
Explanation:
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.
NEW QUESTION # 36
What happens whenCollect recordsis enabled on an Automated Indicator form?
Answer: A
Explanation:
WhenCollect recordsis enabled on an Automated Indicator, Platform Analytics stores thesys_ids of the recordsthat contributed to each indicator score at collection time. This capability enablesdrill-down functionality, allowing users to view the exact records behind a score directly from analytics widgets and dashboards. Importantly, Platform Analytics doesnot store full copies of records-only the identifiers- ensuring historical accuracy while maintaining storage efficiency.
Option A describes thepreview featureavailable when defining indicator conditions, not record collection.
Option B refers tomanual data collection, which is triggered separately. Option C is incorrect because Platform Analytics does not retain full record snapshots. ServiceNow documentation clearly states that enabling Collect records allows analytics users to drill into the contributing records for any given score, making option D the correct and precise answer.
NEW QUESTION # 37
What should thetargetfor theIndexand its supporting indicators be set to when creating anIndex Indicator?
Answer: C
Explanation:
AnIndex Indicatorin Platform Analytics represents a composite score calculated from multiple supporting indicators. According to ServiceNow best practices, both theIndex and its supporting indicatorsshould be normalized so thathigher values represent better performance. Therefore, the correct configuration is a target of 100%with aMaximizedirection.
This standardization ensures consistent weighting and scoring logic across all contributing indicators. If supporting indicators were set to Minimize or had inconsistent targets, the index calculation would produce misleading or inverted results. Options involving a 0% target are incorrect because index scores are designed to trend toward full achievement, represented as 100%. ServiceNow documentation clearly states that index indicators assume maximization logic for proper normalization and aggregation, making option D the correct and documented choice.
NEW QUESTION # 38
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