Enrichments

Data Enrichment API

Enhance your datasets with AI-powered enrichments, custom pipelines, and integrated Python notebooks for advanced analytics.

Features

Enrichment Pipelines

Build and manage data enrichment pipelines.

View Pipelines

Pipeline Execution

Execute enrichment pipelines on your datasets.

Execute Pipelines

Python Notebooks

Use Jupyter notebooks for custom enrichments.

View Notebooks

Available Endpoints

Enrichment Management

Core operations for managing enrichment pipelines and configurations.

Method	Endpoint	Description
GET	`/api/{tenantId}/{projectId}/enrichments`	List all enrichment pipelines
POST	`/api/{tenantId}/{projectId}/enrichment`	Create new enrichment pipeline
GET	`/api/{tenantId}/{projectId}/enrichment/{enrichmentId}`	Get enrichment details
PUT	`/api/{tenantId}/{projectId}/enrichment/{enrichmentId}`	Update enrichment configuration
DELETE	`/api/{tenantId}/{projectId}/enrichment/{enrichmentId}`	Delete enrichment pipeline

Pipeline Execution

Execute enrichment pipelines and monitor processing status.

Method	Endpoint	Description
POST	`/api/{tenantId}/{projectId}/enrichment/{enrichmentId}/execute`	Execute enrichment pipeline
GET	`/api/{tenantId}/{projectId}/enrichment/{enrichmentId}/status`	Get execution status
GET	`/api/{tenantId}/{projectId}/enrichment/{enrichmentId}/results`	Get enrichment results

Notebook Integration

Manage Python notebooks for custom enrichment logic.

Method	Endpoint	Description
GET	`/api/{tenantId}/{projectId}/enrichment/notebooks`	List available notebooks
POST	`/api/{tenantId}/{projectId}/enrichment/notebook/execute`	Execute notebook enrichment

Enrichment Types

mindzieStudio supports various types of data enrichment for enhanced process mining analysis:

AI-Powered Enrichments

Leverage artificial intelligence for intelligent data enhancement.

Activity classification
Anomaly detection
Pattern recognition
Predictive insights

Statistical Enrichments

Add calculated metrics and statistical insights.

Duration calculations
Frequency analysis
Performance indicators
Trend analysis

Business Rules

Apply custom business logic and validation rules.

Compliance checking
Business rule validation
Data quality assessment
Custom transformations

External Integration

Enrich data with external system information.

ERP data lookup
CRM integration
Third-party APIs
Master data enrichment

Pipeline Configuration

Understanding enrichment pipeline structure and configuration options:

Basic Pipeline Structure

{
  "enrichmentId": "enrich-550e8400-e29b-41d4-a716-446655440000",
  "name": "Process Performance Enrichment",
  "description": "Calculate KPIs and performance metrics",
  "type": "statistical",
  "inputDataset": "dataset-660e8400-e29b-41d4-a716-446655440000",
  "steps": [
    {
      "stepId": "step-001",
      "type": "duration_calculation",
      "config": {
        "fromActivity": "Order Created",
        "toActivity": "Order Completed",
        "outputColumn": "TotalDuration"
      }
    },
    {
      "stepId": "step-002",
      "type": "frequency_analysis",
      "config": {
        "groupBy": "Activity",
        "outputColumn": "ActivityFrequency"
      }
    }
  ],
  "schedule": {
    "enabled": true,
    "frequency": "daily",
    "time": "02:00"
  }
}

Common Use Cases

Process Intelligence: Add AI-powered insights and pattern recognition to event logs
Performance Analysis: Calculate KPIs, durations, and performance metrics automatically
Data Quality: Validate and clean process data using business rules
Compliance Monitoring: Check adherence to business rules and regulations
Predictive Analytics: Generate predictions for process outcomes and bottlenecks
External Context: Enrich process data with information from other business systems

Note: All Enrichment API endpoints require valid authentication with appropriate permissions for the target project and tenant.

Get Started: Begin with Pipeline Management to create enrichment pipelines, then explore Pipeline Execution for running enrichments on your datasets.