Core Components

Metric Framework

• Metric Definition Table (sn_getwell_metric ): Stores information about each metric, including thresholds, weights, and configuration
• Execution Statistics (sn_getwell_metric_execution_stats ): Tracks runtime statistics for each metric execution
• Activation Audit (sn_getwell_metric_activation_audit ): Records when metrics are activated or deactivated

Data Collection

• Scheduled Jobs for Metric Calculation:

  • CMDB Metric Collection Scheduled Job: Calculates CMDB-related metrics
    
  • CSDM Metric Collection Scheduled Job: Calculates CSDM-related metrics

• Performance Analytics (PA) Jobs:

  • CMDB Data Foundations PA Metric Collection: Populates PA indicators for CMDB metrics
    
  • CSDM Data Foundations PA Metric Collection: Populates PA indicators for CSDM metrics

• Script Includes:

Each metric has an associated script include that contains the actual logic to calculate the metric result

Visualization Components

• Performance Analytics (PA) Indicators: Connect to the metric data to provide trending information
• Dashboard Widgets: Display the metric results and trends through various visualizations (bar charts, list views, scores)

How It All Works Together

Data Collection and Scoring Process:

1. Scheduled Job Execution
   

• Regular metric calculation jobs run daily
  

• Each job invokes the appropriate script includes to calculate metrics

  1. Metric Calculation
     

• Each metric has a dedicated script include file

• The script runs queries against ServiceNow tables to evaluate compliance

• Results are stored in specific metric result tables (like sn_getwell_hardware_ci_class)

  1. Score Aggregation
     

• Metric results are weighted and aggregated to produce overall scores

• These scores are stored in sn_getwell_cmdb_score and sn_getwell_csdm_score tables

Performance Analytics Integration:

1. PA Jobs
   

• CMDB Data Foundations PA Metric Collection and CSDM Data Foundations PA Metric Collection jobs
  
• Run separately from the metric calculation jobs
  
• Process the data from metric result tables and feed it into PA indicators
  

• Calculate time-based trends and historical comparisons

  1. Trend Analysis
     

• Track compliance over time

• Show historical patterns for non-compliant records

• Provide visibility into improving or declining metrics

Dashboard Visualization:

1. Real-time Views
   

• Current scores and non-compliant items are displayed
  

• Categories are organized by tabs (Best Practices, Customizations, Data Management Practices)

  1. Trending Views
     

• PA indicators populated by the PA jobs show metric trends over time

• Allow visualization of improvements or degradation in compliance

Complete Workflow

1. The regular scheduled jobs ( CMDB Metric Collection and CSDM Metric Collection) run to calculate current metrics
2. Script includes calculate individual metrics (e.g., "CIs Missing Serial Numbers")
3. Results are stored in appropriate tables
4. Overall scores are updated in score tables
5. The PA jobs (CMDB Data Foundations PA Metric Collection and CSDM Data Foundations PA Metric Collection) run to:
   
   • Process the current metric data
     
   • Update trending information in PA indicators
     
   • Calculate historical comparisons
6. Dashboard widgets reflect both:
   
   • The latest data from the metric calculation
     
   • Historical trends from the PA jobs

Additional Resources

Landing page

CMDB Data Foundations Dashboard product documentation

CSDM Data Foundations Dashboard product documentation

CMDB and CSDM Data Foundations Dashboard common error scenarios

Next Step

CMDB and CSDM Data Foundations Dashboard Performance