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

  • Release version: Zurich
  • Updated May 25, 2026
  • 5 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 powerful tool for CMDB administrators to monitor and improve the quality of Configuration Management Database (CMDB) data. It focuses on principal CI classes and highlights data quality issues such as attribute completeness, stale records, and duplicates. The dashboard provides actionable insights through visual metrics, AI-generated summaries, and remediation guidance to help maintain accurate and reliable CMDB data aligned with Data Foundations best practices.

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    Key Features

    • AI-Generated Data Quality Insights: The dashboard includes an AI-powered summary that ranks the top five data quality issues affecting the CMDB, prioritizing foundational problems like duplicates and stale CIs. This summary helps focus remediation efforts effectively.
    • Principal Class and Data Source Breakdown: Visual charts display the distribution of operational CIs by principal classes and data integration sources, enabling administrators to understand data population and coverage.
    • Attribute Completeness Metrics: The dashboard identifies CI classes missing key attributes, such as name, managed by group, or location, highlighting areas needing data enrichment.
    • Data Quality Issues Monitoring: Metrics track stale CIs that have not been updated within defined maintenance windows and detect duplicate CIs, both of which can compromise CMDB accuracy and impact incident and change management.
    • Filters for Targeted Analysis: Administrators can refine dashboard data by selecting specific principal classes, date ranges, and thresholds for stale CIs to focus on relevant subsets of data quality issues.
    • Remediation Actions Panel: When available, this panel guides users through steps to resolve identified data quality problems, facilitating continuous CMDB improvement.

    Access and Roles

    The dashboard is accessible from the CMDB success advisor landing page after completing the Data Foundations setup process. Access requires the sncmdbadmin role for full dashboard capabilities, while the sncmdbuser role provides read-only access including viewing AI summaries.

    Practical Use Cases

    • Monitor completeness of CI attributes across key classes to ensure data integrity.
    • Identify and prioritize classes with low data quality scores and those affected by stale or duplicate records.
    • Evaluate integration coverage to verify correct data sources populate the CMDB.
    • Use incident, change, and problem impact data to prioritize remediation efforts efficiently.
    • Track progress toward alignment with the Common Service Data Model (CSDM).

    Key Outcomes

    By regularly monitoring the dashboard and acting on the recommended remediation steps, ServiceNow customers can systematically enhance CMDB data quality, leading to more accurate configuration data. This improves operational decision-making, incident and change impact analysis, and overall ServiceNow platform reliability.

    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:
    Charts display up to the top 10 values. Any remaining values are grouped into an Others category. 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. The dashboard header displays a Last updated timestamp reflecting the completion time of the most recent Data Foundations data collector job run.

    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.
    sn_cmdb_user Provides read-only access to CMDB success advisor pages and data, including the AI-generated summary of the 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
    CMDB data quality insights generated by AI Displays an AI-generated summary of CMDB data quality for Data Foundations outcomes and lists the top 5 issues with guided remediation actions.

    Issues are ranked primarily by the percentage of CIs or CI classes that each issue affects, not by severity, within four categories, in this order: Data Integrity, Key Attributes, Reconciliation & Governance, and Data Manager Policies. Foundational data integrity issues, such as duplicate CIs and stale CIs, are evaluated first because they can inflate the counts behind other issues.

    A percentage gap of more than 15 points between issues in the same category can change their default order. A percentage gap of more than 40 points between issues in different categories can also change their default order. For the reasoning behind the ranking and recommendations, see Summarize CMDB readiness with the ServiceNow Otto skill.

    Note:
    Available only when the summarize CMDB readiness skill is configured. See Configure the summarize CMDB readiness skill.
    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

    Filters enable 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