Monitoring CMDB data quality using dashboard metrics in CMDB success advisor for Data Foundations

  • Release version: Yokohama
  • Updated May 25, 2026
  • 4 minutes to read
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    Summary of Monitoring CMDB data quality using dashboard metrics in CMDB success advisor for Data Foundations

    The CMDB success advisor for Data Foundations dashboard is a tool designed for CMDB administrators to monitor and improve data quality within the Configuration Management Database (CMDB). It focuses on principal CI (Configuration Item) classes, helping identify issues such as missing attributes, stale records, and duplicates that affect CMDB accuracy and reliability. The dashboard supports informed remediation efforts and tracks progress toward CSDM alignment.

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    Access and Requirements

    • Accessible via the CMDB success advisor landing page after completing setup.
    • Requires the sncmdbadmin role to view the Data Foundations dashboard.

    Key Features

    • Interactive Metrics and Charts: Visual breakdowns of operational CIs by principal class and integration source.
    • Data Quality Indicators: Highlight missing key attributes such as name, managed by group, and location for CIs.
    • Stale and Duplicate CI Detection: Identifies CIs not updated within selected timeframes and potential duplicates.
    • Filters: Allow narrowing data by principal classes, date range, and stale CI thresholds (7, 14, 30, 60, 90 days).
    • KPI Details and Remediation Actions: Selecting chart segments opens detailed trend analysis and remediation guidance to improve CMDB quality.

    Practical Use Cases for ServiceNow Customers

    • Monitor completeness of CI attributes across key classes to ensure data integrity.
    • Identify classes at risk due to low data quality scores for targeted improvements.
    • Detect and resolve stale or duplicate CIs to maintain accurate and current CMDB records.
    • Evaluate integration source coverage to verify appropriate data population in the CMDB.
    • Prioritize remediation based on impact from incidents, changes, and problems.
    • Track alignment progress with the Common Service Data Model (CSDM).

    Important Notes

    • Dashboard data respects selected filters for principal classes and date ranges to focus insights.
    • If Performance Analytics data collector hits row limits, some metrics may not load, indicated by a notification banner.
    • Use the remediation panel for actionable steps to address identified data quality issues.

    The CMDB success advisor for Data Foundations dashboard enables CMDB administrators to identify and address data quality issues specific to principal classes in the Configuration Management Database (CMDB).

    Important:
    When you select a segment or count on a chart from a CMDB success advisor dashboard, the KPI Details page opens. On the page, you can analyze how a specific metric trends over time. Additionally, the Remediation actions panel appears when remediation actions are available for that card. Use the panel to improve the quality of CMDB. To learn more, see KPI Details and Improving CMDB data quality for Data Foundations.
    CMDB success advisor for Data Foundations dashboard overview.
    Note:
    If the Performance Analytics data collector exceeds its row limit during data processing, a notification banner appears on the dashboard indicating that some metrics could not be loaded. For more information, see Data collector Performance Analytics properties.

    Access the dashboard

    To open the dashboard, select View insights for Data Foundations on the CMDB success advisor landing page. See Access CMDB success advisor.

    Note:
    The CMDB success advisor for Data Foundations dashboard is available only after the setup process is complete. For more information, see CMDB success advisor for Data Foundations setup.

    Required roles

    Table 1. Roles required for CMDB success advisor for Data Foundations dashboard
    Role Description
    sn_cmdb_admin Required to access the Data Foundations dashboard.

    Use cases

    For examples of how different people in your organization would use this dashboard, see these use cases.

    User Dashboard use
    CMDB administrator
    • Monitor CI attribute completeness across principal classes
    • Identify classes at risk with low data quality scores
    • Detect stale and duplicate CI records affecting CMDB data accuracy
    • Evaluate integration coverage to ensure the right sources are populating the CMDB
    • Prioritize remediation efforts based on incident, change, and problem impact
    • Track progress toward CSDM alignment

    Dashboard features

    The dashboard provides clear, consolidated insights into principal CI class data quality and completeness. Use the dashboard to identify and resolve data quality issues within the CMDB through dedicated sections, filters, indicators, and visual reports. Gain valuable insights into CMDB performance related to Data Foundations. Targeted CMDB metrics focus remediation efforts. Regularly monitor these metrics and follow suggested remediation actions to systematically improve CMDB data quality over time.

    Important:
    The dashboard data is filtered based on the Selected principal classes and Date range filters. See Filters.
    Table 2. Feature description
    Feature Description
    CIs by principal class Displays the breakdown of operational CIs by principal CI class to highlight CI distribution in the CMDB.
    CIs by data integration source Displays the breakdown of operational CIs by data integration source to highlight their contribution to CMDB population.
    CIs missing key attributes Displays completeness metrics per principal CI class, identifying classes below the defined threshold.
    CI data quality issues Displays key metrics related to CIs that have not been updated or may have duplicate records, leading to outdated information and inconsistencies in the CMDB.

    Filters

    Enables narrowing the data shown in graphs and metrics based on principal class, date range, or stale CI threshold.

    Name Type Description
    Principal classes List Filters CIs based on the selected principal classes.
    Date range Date Filters the dashboard data based on the selected date range.
    Stale CI List Filters stale CIs based on the number of days since their last update. Available values: 7, 14, 30, 60, and 90 days.

    CIs missing key attributes

    Key metrics for the completeness of CI attributes across principal classes, identifying gaps that affect data quality.

    Card Description Indicators
    CIs missing name Total number of CI records from principal classes missing a name, measured daily, where the CI does not have a name specified. DF CIs missing name
    CIs missing managed by group Total number of CI records from principal classes missing a managed by group, measured daily, where the CI does not have a managed by group assigned. DF CIs missing managed by group
    CIs missing location Total number of CI records from principal classes missing a location, measured daily, where the CI does not have a location assigned. DF CIs missing location

    CI data quality issues

    Key metrics for CIs that have not been updated or may have duplicate records, leading to outdated information and inconsistencies in the CMDB.

    Card Description Indicators
    Stale CIs Principal class CIs not updated within the expected maintenance window, causing data gaps and inaccuracies that affect incident and change impact analysis. Additionally filtered by the Stale CI filter.

    When you select a segment on the Stale CIs chart, the KPI Details page title reflects the Stale CI filter value selected at the time (for example, "CIs not updated in last 30 days").

    		 DF CIs not updated in last 7 days

    DF CIs not updated in last 14 days

    DF CIs not updated in last 30 days

    DF CIs not updated in last 60 days

    DF CIs not updated in last 90 days

    Note:
    The CIs not updated card data is additionally filtered based on the Stale CI filter. See Filters.
    Duplicate CIs Operational CIs identified as duplicates within principal classes, causing ambiguous CI selection in processes and data redundancy. DF duplicate CIs