Metrics for Collate

Metrics in Collate

The Metrics entity in Collate allows users to define, track, and manage key business and operational metrics. Metrics help organizations maintain consistency, traceability, and accuracy in data-driven decision-making.

Overview of Metrics

Metrics represent calculated values based on data assets and are categorized under the Governance section in Collate. Each metric can be linked to glossary terms, data assets, and other metrics, providing comprehensive visibility into data quality and usage.

Key Properties of a Metric

Property	Description	Example Value
Name	Unique identifier for the metric, following camelCase naming conventions.	customerRetentionRate
Display Name	Human-readable name for the metric.	Customer Retention Rate
Description	Detailed explanation of what the metric represents.	Percentage of retained users
Expression	Formula or SQL query used to calculate the metric.	COUNT(returning_customers)
Granularity	Time scale for the metric, such as daily, weekly, or monthly.	Daily
Metric Type	Type of calculation applied to the metric (e.g., count, average, ratio).	Percentage
Unit of Measurement	Unit for interpreting metric values, such as count, dollars, or percentage.	Percentage
SQL Query	Optional SQL query defining the metric.	SELECT COUNT(*) FROM sales
Owner	Individual or team responsible for maintaining the metric.	Data Governance Team

Metric Lineage and Dependencies

Collate allows users to trace the source and dependencies of metrics using lineage. This ensures end-to-end traceability from raw data to metric reporting. A typical lineage might look like:

Database Table → Metric → Pipeline → Dashboard

Users can view associated tables, pipelines, and dashboards to understand how metrics are generated and utilized.

Creating Metrics Using the UI

To create a new metric in Collate using the user interface, follow these steps:

1. Navigate to the Metrics Section

• Go to Govern > Metrics in the Collate UI.

2. Add a New Metric

• Click on Add Metric to initiate the metric creation process.

3. Enter Metric Details

Provide the required information, including:

• Metric Name
• Description
• Granularity (time scale of the metric)
• Metric Type (e.g., count, average, ratio)
• Computation Code (SQL, Python, or Java) if applicable

4. Create the Metric

• After entering the details, click Create to finalize the metric.

5. View the Created Metric

• The newly created metric will now be available in the Metrics page for reference and further use.

Example JSON Schema for Metric

{
  "id": "123e4567-e89b-12d3-a456-426614174000",
  "name": "customerRetentionRate",
  "displayName": "Customer Retention Rate",
  "description": "Percentage of customers retained over a given period.",
  "formula": "COUNT(returning_customers) / COUNT(total_customers) * 100",
  "sql": "SELECT COUNT(*) FROM customer_activity WHERE status='active'",
  "granularity": "Monthly",
  "metricType": "Percentage",
  "unit": "Percentage",
  "owner": "Data Governance Team",
  "tags": ["Customer", "KPI", "Retention"]
}

Managing Metrics in Collate

• Versioning: Each update to a metric creates a new version, maintaining historical changes.
• Linking: Metrics can be linked to glossary terms, tables, dashboards, and pipelines for enriched context.
• Monitoring: Metrics can be monitored for value changes, enabling trend analysis over time

Best Practices for Metric Management

• Consistent Naming: Use camelCase for metric names to ensure consistency across systems.
• Clear Definitions: Provide comprehensive descriptions and units for accurate interpretation.
• Lineage Tracking: Always associate metrics with source tables and pipelines for traceability.
• Ownership: Assign metric owners for accountability and maintenance.