Integration Use Cases

This page presents five practical use cases demonstrating how Orthogramic 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": "businessCapability",
        "propertyType": "string",
        "description": "Orthogramic capability ID"
      },
      {
        "name": "capabilityName",
        "propertyType": "string",
        "description": "Human-readable capability name"
      },
      {
        "name": "capabilityOwner",
        "propertyType": "string",
        "description": "Business owner of the capability"
      }
    ]
  }
}

Step 2: Apply to Data Assets

{
  "table": {
    "fullyQualifiedName": "warehouse.crm.customers",
    "displayName": "Customer Master",
    "customProperties": {
      "businessCapability": "CAP-CRM-001",
      "capabilityName": "Customer Relationship Management",
      "capabilityOwner": "Sales Division"
    }
  }
}

Step 3: Query by Capability

-- OpenMetadata search query
SELECT * FROM tables 
WHERE customProperties.businessCapability = '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 Orthogramic

{
  "valueStream": {
    "valueStreamID": "VS-ORDER-001",
    "title": "Order to Cash",
    "stages": [
      {
        "stageID": "stage-order",
        "name": "Order Capture",
        "description": "Receive and validate customer orders"
      },
      {
        "stageID": "stage-fulfill",
        "name": "Fulfillment",
        "description": "Pick, pack, and ship orders"
      },
      {
        "stageID": "stage-invoice",
        "name": "Invoicing",
        "description": "Generate and send invoices"
      },
      {
        "stageID": "stage-collect",
        "name": "Collection",
        "description": "Receive and reconcile payments"
      }
    ]
  }
}

Step 2: Tag OpenMetadata Pipelines

{
  "pipeline": {
    "fullyQualifiedName": "airflow.order_processing",
    "displayName": "Order Processing Pipeline",
    "customProperties": {
      "businessValueStream": "VS-ORDER-001",
      "valueStreamStage": "stage-order",
      "businessValue": "Order capture automation"
    }
  }
}

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 Orthogramic stakeholders, creating a complete accountability chain.

Implementation

Step 1: Define Stakeholder in Orthogramic

{
  "stakeholder": {
    "stakeholderID": "STK-CFO-001",
    "title": "Chief Financial Officer",
    "stakeholderType": "individual",
    "email": "cfo@company.com",
    "accountabilities": [
      "Financial Reporting",
      "Budget Management",
      "Investment Decisions"
    ],
    "dataAccountabilities": [
      "Finance data quality",
      "Financial KPI accuracy"
    ]
  }
}

Step 2: Link to OpenMetadata User

{
  "user": {
    "name": "cfo",
    "displayName": "Chief Financial Officer",
    "email": "cfo@company.com",
    "teams": ["finance-leadership", "data-governance-council"],
    "customProperties": {
      "businessStakeholder": "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 Orthogramic policies to OpenMetadata governance rules with automated enforcement.

Implementation

Step 1: Define Policy in Orthogramic

{
  "policy": {
    "policyID": "POL-DATA-001",
    "title": "Customer Data Retention Policy",
    "policyType": "data-governance",
    "scope": "All customer PII",
    "requirements": [
      {
        "requirementID": "req-retention",
        "description": "Delete customer PII after 730 days",
        "enforcement": "mandatory",
        "exception": "Legal hold overrides"
      }
    ],
    "owner": "Chief Privacy Officer",
    "effectiveDate": "2024-01-01"
  }
}

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": {
      "businessPolicy": "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 Orthogramic's Strategic Response Model to trigger OpenMetadata data quality test suites and alerts.

Implementation

Step 1: Define Trigger in Orthogramic

{
  "trigger": {
    "triggerID": "TRG-REG-001",
    "label": "GDPR Audit Notification",
    "category": "Regulatory or compliance",
    "source": "regulatory-publication",
    "description": "Annual GDPR compliance audit scheduled",
    "urgency": "high",
    "response": {
      "responseType": "data-quality-validation",
      "actions": [
        "Validate PII classification completeness",
        "Run data quality tests on customer tables",
        "Generate compliance report"
      ]
    }
  }
}

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": {
      "businessTrigger": "TRG-REG-001",
      "triggerType": "regulatory-audit"
    }
  }
}

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": {
      "businessTrigger": "TRG-REG-001"
    }
  }
}

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