Extended analysis

  • Release version: Zurich
  • Updated September 16, 2025
  • 3 minutes to read
  • Summarize
    Summarized using AI
    This content was generated using new OpenAI-powered functionality. Results are provided on an as is basis and are not guaranteed to be accurate or complete.

    Summary of Extended analysis

    Extended analysis in ServiceNow's Zurich release provides a deeper level of data exploration by aggregating related records and examining Choice, Reference, and Boolean columns within relevant tables. This advanced analysis uncovers new insights, enabling more informed decision-making by analyzing more granular data characteristics beyond standard analysis.

    Show full answer Show less

    How Extended Analysis Works

    • It aggregates records linked to a response in an exploration, focusing on the columns visible in the record list and related tables.
    • The number of columns analyzed is controlled by the system property snquerygen.hiddeninsights.groupby.minfields, defaulting to 5.
    • If fewer than the set number of eligible columns are visible, the system searches for additional Choice, Reference, and Boolean fields on the table, prioritizing fields with the highest cardinality to reach the minimum field count.
    • Extended analysis generates unique insights by avoiding repetition and automatically drilling down into interesting data subsets for faster, more specific results.
    • This feature requires the analytics hidden insight skill from Query Generation to be active.
    • Users enable extended analysis by selecting it in the Ask Now Assist or AI Data Explorer interfaces.

    Benefits for ServiceNow Customers

    • Generates unique, deeper insights without needing multiple follow-up queries.
    • Automatically focuses on the most relevant data segments, improving efficiency and response speed.
    • Provides richer contextual information, such as trends, shifts, and variability in data, enhancing operational understanding.
    • Allows customers to tailor the depth of analysis by selecting which fields to display, influencing the quality and scope of insights.

    Comparison: Standard vs. Extended Analysis

    Standard analysis provides high-level summaries and trends, such as peak incident volumes and overall counts. Extended analysis adds detailed metrics including percentage changes, trend slopes, and statistical measures like standard deviation, offering a more comprehensive view of data fluctuations and operational dynamics.

    Considerations

    • Extended analysis consumes more system resources and takes longer to process than standard analysis; customers should use it judiciously.
    • If no eligible fields are found, extended analysis is not performed.

    Generate a deeper level of analysis that can reveal new insights, enabling you to make more informed decisions.

    Extended analysis involves aggregating the records related to a response in an exploration. It examines the same columns that you see when you view the list of records for the relevant table. It takes a Count of Choice, Reference, and Boolean columns. Therefore, you can influence extended analysis by selecting which fields to view in the relevant tables. The relevant tables include any related tables that Query Generation dot-walks to.

    The number of columns that extended analysis examines is set in the system property sn_query_gen.hidden_insights.groupby.min_fields. The default value is 5. If the number of eligible columns that are visible on the record list is lower than this value, the system searches for more fields on the table. The search stops when the total number of fields from both the list view and the table search reaches the value of the system property. If the system can’t find that many fields, it uses the fields it does find.

    The search for fields on the table follows this logic:
    1. The system searches for Choice fields on the table.
    2. If the count of located Choice fields and eligible columns on the record list is greater than the value of sn_query_gen.hidden_insights.groupby.min_fields, not all located Choice fields are selected. Instead, the system selects the Choice fields with the highest cardinality, to bring the total count of fields up to the value of the property. The search then stops.
    3. If the system can’t find enough Choice fields to bring the total count of fields up to the value of the property, the system selects the ones it finds, then looks for Reference fields. The same logic that was used for selecting Choice fields applies.
    4. If the system can’t find enough Reference fields to bring the total count of fields up to the value of the property, the system selects the ones it finds, then looks for Boolean fields. The same logic that was used for selecting Choice and Reference fields applies.
    5. Extended analysis insights are generated for however many Choice, Reference, and Boolean fields are found, up to the value of the property. If no fields are found, extended analysis isn’t performed.

    While the results of extended analysis usually enrich the responses in an exploration, the analysis takes more time and uses more system resources than a standard analysis. You have to use your judgment on when to employ it.

    Sometimes different questions or follow-up questions return the same extended analysis findings. Instead of repeating those findings as insights, the system digs deeper into the underlying reasons for the repetition. As a user, you have three benefits from this approach:
    • Every insight that is generated is unique.
    • You don't need to posit as many follow-up questions to get the insights you need, because the system drills down automatically, directing you to the interesting part of the data to focus on.
    • Results are faster, because extended analysis focuses on an increasingly specific subset of the data.

    Extended analysis requires the analytics hidden insight skill from Query Generation to be active. For more information, see Query Generation skills.

    To turn on extended analysis for an exploration, select it in the Ask Now Assist a question about data field. You have the same choice when you launch AI Data Explorer in a data visualization or list.
    Selecting extended or standard analysis.

    Standard vs. extended analysis

    Consider the following request made in an exploration: "Analyze the incident creation trend over the past 12 months." Using standard analysis, you get the following insights: "Incident creation peaked in July 2025 with 2,441 incidents, while the lowest monthly count was 1,177 incidents in August 2025. The first half of the period (September 2024 to February 2025) saw monthly incident counts consistently above 1,700, but the final month dropped by more than 50% compared to the peak."

    Figure 1. Insights from standard analysis
    Resulting insights from a standard analysis of the request to analyze the incident creation trend over the past 12 months.
    Making the same request with extended analysis, you get the same insight plus the following information:
    • Incident volume dropped 49.2% from 2,441 in July 2025 to 1,177 in August 2025, indicating a major shift.

    • The largest monthly increase was 28.3% in April 2025, with incidents rising by 512 to 2,321.

    • Incident counts show a consistent downward trend (slope: -24.22), which suggests an ongoing reduction in reported issues.

    • Monthly incident counts vary widely (range: 1,264; standard deviation: 369.24), indicating unstable operational demand.

    Figure 2. Insights from extended analysis
    Resulting insights from an extended analysis of the request to analyze the incident creation trend over the past 12 months.