Integration Use Cases
This page presents five practical use cases demonstrating how Triodian and OpenMetadata integration creates business value. Each use case includes the problem, solution pattern, and implementation example.
Use Case 1: Linking Business Capabilities to Data Assets
The Problem
Data engineers document tables in OpenMetadata, but there's no connection to business capabilities. When business stakeholders ask "What data supports our Customer Onboarding capability?", the answer requires manual investigation.
The Solution
Add business capability context to OpenMetadata data assets using custom properties, enabling queries like "Show all tables supporting capability X."
Implementation
Step 1: Define Custom Properties
{
"customPropertyConfig": {
"entityType": "table",
"properties": [
{
"name": "capabilityID",
"propertyType": "string",
"description": "Triodian capabilityID"
},
{
"name": "capabilityTitle",
"propertyType": "string",
"description": "The capability's Triodian title"
},
{
"name": "capabilityOwner",
"propertyType": "string",
"description": "The capability's Triodian owner"
}
]
}
}
Step 2: Apply to Data Assets
{
"table": {
"fullyQualifiedName": "warehouse.crm.customers",
"displayName": "Customer Master",
"customProperties": {
"capabilityID": "CAP-CRM-001",
"capabilityTitle": "Customer Relationship Management",
"capabilityOwner": "Sales Division"
}
}
}
Step 3: Query by Capability
-- OpenMetadata search query
SELECT * FROM tables
WHERE customProperties.capabilityID = 'CAP-CRM-001'
Business Value
| Benefit | Description |
|---|---|
| Impact analysis | Understand data impact when capabilities change |
| Investment justification | Link data platform costs to business capabilities |
| Capability assessment | Identify data gaps in capability support |
| Accountability | Clear ownership chain from data to business |
Use Case 2: Tracing Value Streams to Data Pipelines
The Problem
Business value streams (like Order-to-Cash) span multiple systems and data pipelines. When the Invoicing stage has issues, it's unclear which data pipelines are affected.
The Solution
Map value stream stages to OpenMetadata pipelines, creating business-to-technical traceability.
Implementation
Step 1: Model Value Stream in Triodian
The value stream is one record:
{
"valueStreamID": "VS-ORDER-001",
"title": "Order to Cash",
"description": "From receiving a customer order to collecting payment",
"purpose": "Turn customer orders into realised revenue",
"owner": "Chief Operating Officer"
}
Each stage is a Value Stream Stage record that points to the value stream with parentValueStreamID:
[
{
"stageID": "VSS-ORDER-01",
"stageTitle": "Order Capture",
"parentValueStreamID": "VS-ORDER-001",
"description": "Receive and validate customer orders"
},
{
"stageID": "VSS-ORDER-02",
"stageTitle": "Fulfillment",
"parentValueStreamID": "VS-ORDER-001",
"description": "Pick, pack, and ship orders"
},
{
"stageID": "VSS-ORDER-03",
"stageTitle": "Invoicing",
"parentValueStreamID": "VS-ORDER-001",
"description": "Generate and send invoices"
},
{
"stageID": "VSS-ORDER-04",
"stageTitle": "Collection",
"parentValueStreamID": "VS-ORDER-001",
"description": "Receive and reconcile payments"
}
]
Step 2: Tag OpenMetadata Pipelines
{
"pipeline": {
"fullyQualifiedName": "airflow.order_processing",
"displayName": "Order Processing Pipeline",
"customProperties": {
"valueStreamID": "VS-ORDER-001",
"stageID": "VSS-ORDER-01",
"stageTitle": "Order Capture"
}
}
}
Step 3: Create Value Stream View
Business Value
| Benefit | Description |
|---|---|
| Root cause analysis | Trace business issues to data pipelines |
| Change impact | Understand business impact of pipeline changes |
| SLA alignment | Link pipeline SLAs to business value delivery |
| Investment prioritization | Focus on pipelines supporting critical value stages |
Use Case 3: Mapping Business Stakeholders to Data Ownership
The Problem
Data ownership in OpenMetadata uses technical team names. Business stakeholders don't know who's accountable for data quality from a business perspective.
The Solution
Link OpenMetadata ownership to Triodian stakeholders, creating a complete accountability chain.
Implementation
Step 1: Define Stakeholder in Triodian
{
"stakeholderID": "STK-CFO-001",
"title": "Chief Financial Officer",
"tType": "employeeStaff",
"description": "Executive accountable for the organisation's finances",
"role": "Financial reporting, budget management and investment decisions; accountable for finance data quality and financial KPI accuracy",
"stakeholderCategory": "internalStakeholder",
"orgUnitTitle": "Finance Leadership",
"orgUnitID": "OU-FIN-LEAD",
"influenceLevel": "highInfluence",
"interestLevel": "highInterest"
}
Triodian stakeholder records carry no contact details; the e-mail address comes from your identity directory.
Step 2: Link to OpenMetadata User
{
"user": {
"name": "cfo",
"displayName": "Chief Financial Officer",
"email": "cfo@company.com",
"teams": ["finance-leadership", "data-governance-council"],
"customProperties": {
"stakeholderID": "STK-CFO-001",
"accountabilityDomains": ["finance", "performance"]
}
}
}
Step 3: Assign as Data Owner
{
"domain": {
"name": "finance",
"displayName": "Finance Domain",
"owner": {
"type": "user",
"name": "cfo"
},
"experts": [
{"type": "user", "name": "finance-data-steward"}
]
}
}
Business Value
| Benefit | Description |
|---|---|
| Clear accountability | Business leaders own their data domains |
| Escalation paths | Know who to contact for data issues |
| Governance alignment | Data governance reflects business structure |
| Audit readiness | Document ownership for compliance |
Use Case 4: Policy-Driven Data Governance
The Problem
Business policies exist in documents but aren't enforced in data platforms. A "Customer Data Retention Policy" says delete after 2 years, but nothing prevents data from persisting longer.
The Solution
Translate Triodian policies to OpenMetadata governance rules with automated enforcement.
Implementation
Step 1: Define Policy in Triodian
{
"policyID": "POL-DATA-001",
"title": "Customer Data Retention Policy",
"description": "Limits how long customer personal data is kept",
"purpose": "Comply with data protection law and reduce privacy risk",
"scope": "All customer PII",
"enforcedBy": "Data Governance Office",
"owner": "Chief Privacy Officer",
"requirements": "Delete customer PII after 730 days (mandatory); legal hold overrides",
"complianceMetrics": "Share of customer tables with no PII older than 730 days",
"reviewFrequency": "Annually, effective from 1 January 2024"
}
Step 2: Create OpenMetadata Policy
{
"policy": {
"name": "customer-data-retention",
"fullyQualifiedName": "governance.customer-data-retention",
"description": "Enforce customer data retention limits per business policy POL-DATA-001",
"policyType": "Lifecycle",
"enabled": true,
"rules": [
{
"name": "PII Retention Limit",
"description": "Prevent PII retention beyond 730 days",
"effect": "deny",
"operations": ["All"],
"resources": ["table"],
"condition": "matchAnyTag('PII', 'CustomerData') && daysSinceCreated > 730"
}
],
"customProperties": {
"policyID": "POL-DATA-001",
"policyOwner": "Chief Privacy Officer"
}
}
}
Step 3: Tag Covered Assets
{
"table": {
"fullyQualifiedName": "warehouse.customer.profiles",
"tags": [
{"tagFQN": "Classification.PII"},
{"tagFQN": "DataType.CustomerData"},
{"tagFQN": "Policy.customer-data-retention"}
]
}
}
Business Value
| Benefit | Description |
|---|---|
| Policy enforcement | Business rules actually enforced |
| Compliance automation | Reduce manual compliance checks |
| Audit evidence | Demonstrate policy implementation |
| Risk reduction | Prevent policy violations proactively |
Use Case 5: Strategic Triggers to Data Quality Alerts
The Problem
Business events (like regulatory audits or strategic initiatives) require data quality responses, but there's no connection between business triggers and data platform actions.
The Solution
Use Triodian's Strategic Response Model to trigger OpenMetadata data quality test suites and alerts.
Implementation
Step 1: Define Trigger in Triodian
{
"triggerID": "TRG-002",
"label": "GDPR Audit Notification",
"description": "Annual GDPR compliance audit scheduled",
"primaryCategory": "regulatoryCompliance",
"origin": "External",
"timeHorizon": "immediate",
"impactLevel": "high",
"detectionMethod": "Regulatory publication",
"affectedEntities": [
{
"domainType": "information",
"entityID": "INF-CUST-001",
"title": "Customer Master"
},
{
"domainType": "policy",
"entityID": "POL-DATA-001",
"title": "Customer Data Retention Policy"
}
]
}
The actions taken in response are a Strategic Response that refers back to the trigger:
{
"responseID": "RSP-GDPR-2025",
"responseTitle": "GDPR Audit Data Validation",
"responseType": "complianceProgram",
"responseDescription": "Validate PII classification completeness, run data quality tests on customer tables and generate a compliance report",
"triggerReferences": [
"TRG-002"
],
"affectedDomains": [
"information",
"policy"
],
"status": "inProgress"
}
Step 2: Create OpenMetadata Test Suite
{
"testSuite": {
"name": "gdpr-compliance-validation",
"displayName": "GDPR Compliance Validation",
"description": "Test suite triggered by GDPR audit events",
"testCases": [
{
"name": "pii-classification-complete",
"testDefinition": "columnValuesToBePresentInSet",
"parameterValues": {
"columnValuesToBeInSet": [
"PII",
"Non-PII"
]
}
},
{
"name": "retention-dates-valid",
"testDefinition": "columnValuesToBeBetween",
"parameterValues": {
"minValue": 0,
"maxValue": 730
}
}
],
"customProperties": {
"triggerID": "TRG-002",
"responseID": "RSP-GDPR-2025"
}
}
}
Step 3: Configure Alert
{
"alert": {
"name": "gdpr-audit-alert",
"triggerType": "Scheduled",
"schedule": "0 0 1 * *",
"filteringRules": {
"resources": [
"testSuite:gdpr-compliance-validation"
]
},
"destination": {
"type": "Email",
"config": {
"receivers": [
"compliance@company.com",
"data-governance@company.com"
]
}
},
"customProperties": {
"triggerID": "TRG-002"
}
}
}
Business Value
| Benefit | Description |
|---|---|
| Proactive compliance | Prepare for audits automatically |
| Business-data alignment | Business events drive data actions |
| Reduced manual effort | Automated response to triggers |
| Audit readiness | Always ready for compliance reviews |
Use Case Summary
| Use Case | Business Problem | Integration Solution | Key Benefit |
|---|---|---|---|
| 1 | No capability-data link | Custom properties | Impact analysis |
| 2 | Value stream opacity | Pipeline tagging | Root cause analysis |
| 3 | Ownership confusion | Stakeholder linking | Clear accountability |
| 4 | Policy non-enforcement | Governance rules | Automated compliance |
| 5 | Disconnected triggers | Test suite automation | Proactive response |
Related Documentation
- Entity Mapping — Detailed mapping reference
- Terminology Bridge — Vocabulary translation
- API Patterns — Implementation code