Skip to main content

Home

Monitor your data layer health and track issues in real-time

Dashboard Overview

The dashboard provides a comprehensive overview of your data layer's health and performance. It consists of three main sections:

Monitor Health​

This section displays three key metrics that help you assess the overall health of your data layer:

Data Up Time​

  • Description: Percentage of hours in which any data was measured
  • Color Coding:
    • 🟢 Green: 100% uptime
    • 🟠 Orange: Less than 100% but more than 48 hours
    • 🔴 Red: Less than 48 hours

Event Availability​

  • Description: Percentage of configured events that were actually measured
  • Color Coding:
    • 🟢 Green: 100% availability
    • 🟠 Orange: Between 50% and 100%
    • 🔴 Red: Less than 50%

Data Quality​

  • Description: Percentage of verified data points out of total checked data points
  • Color Coding:
    • 🟢 Green: 90% or higher
    • 🟠 Orange: Between 50% and 90%
    • 🔴 Red: Less than 50%

Issues Overview​

This section provides a summary of issues reported in the last 7 days (excluding today), categorized by priority:

High Priority Issues​

  • New Issues: Shows the number of new high-priority issues that require immediate attention
  • Total Issues: Displays the total number of high-priority issues with a comparison to the previous 7 days
  • Definition: Events or parameters that aren't measured while expected, or parameters that measure values outside of allowed values. Issues are considered high priority if they occur in more than 5% of instances or if the field is marked as 'high priority alert field'

Medium Priority Issues​

  • Total Issues: Shows the total number of medium-priority issues with a comparison to the previous 7 days
  • Definition: Issues worth looking into on short notice, occurring in less than 5% of instances

Low Priority Issues​

  • Total Issues: Displays the total number of low-priority issues with a comparison to the previous 7 days
  • Definition: Issues that clutter your data collection but don't cause immediate breakage (e.g., unexpected events or parameters being measured, or parameters with unexpected JavaScript types)

New Alerts Table​

The alerts table provides detailed information about recent issues:

Table Columns​

  • Date: When the alert was reported
  • Alert Type: The type of issue detected
  • Priority: Issue priority level (High/Medium/Low)
  • Mismatches: Number of mismatches detected
  • Total Occurrences: Total number of times the issue occurred
  • Failure Rate: Percentage of failures (mismatches/total occurrences)

Alert Types​

  • Expected Values: Values set for a field that were not in the list of expected values
  • JavaScript Data Type: Field did not match the expected JavaScript data type
  • Required Fields: Field was not measured even though it was expected
  • Unexpected Fields: Field was measured while it was not expected
  • Unexpected Event: Event was measured while it was not expected
  • Unmeasured Event: Event was not measured even though it was expected
  • Expected Pattern: Field did not match the expected pattern
  • Click on any metric or issue count to navigate to the detailed table view with relevant filters applied
  • Use the table headers to sort the alerts by different criteria
  • Hover over the help icons (🛈) to see detailed explanations of each metric

Best Practices​

  1. Regular Monitoring: Check the dashboard daily to identify and address issues promptly
  2. Priority Management: Focus on high-priority issues first, as they indicate critical problems
  3. Trend Analysis: Use the comparison with previous periods to identify improving or worsening trends
  4. Data Quality: Aim to maintain data quality above 90% for optimal performance