iiRecord
Agentic AI Atlas · incremental-model
lib-process:data-engineering-analytics--incremental-modela5c.ai
II.
LibraryProcess JSON

lib-process:data-engineering-analytics--incremental-model

Structured · live

incremental-model json

Inspect the normalized record payload exactly as the atlas UI reads it.

File · generated-library/processes.yamlCluster · generated-library
Record JSON
{
  "id": "lib-process:data-engineering-analytics--incremental-model",
  "_kind": "LibraryProcess",
  "_file": "generated-library/processes.yaml",
  "_cluster": "generated-library",
  "attributes": {
    "displayName": "incremental-model",
    "description": "Incremental Model Setup - Design and implement incremental models for efficient large-scale data processing,\ncovering incremental strategies (append-only, merge, delete+insert), unique keys, partitioning, clustering, backfill strategies,\nand performance optimization for data warehouse workloads.",
    "libraryPath": "library/specializations/data-engineering-analytics/incremental-model.js",
    "specialization": "data-engineering-analytics",
    "references": [
      "- dbt Incremental Models: https://docs.getdbt.com/docs/build/incremental-models\n- dbt Incremental Strategies: https://docs.getdbt.com/docs/build/incremental-strategy\n- Snowflake Incremental Models: https://docs.getdbt.com/reference/resource-configs/snowflake-configs#merge-behavior-incremental-models\n- BigQuery Incremental Models: https://docs.getdbt.com/reference/resource-configs/bigquery-configs#merge-behavior-incremental-models\n- dbt Performance Best Practices: https://docs.getdbt.com/best-practices/how-we-build-our-metrics/3-optimize-performance"
    ],
    "example": "const result = await orchestrate('specializations/data-engineering-analytics/incremental-model', {\n  projectName: 'analytics_dbt',\n  dataWarehouse: 'Snowflake',\n  modelName: 'fct_orders',\n  sourceModel: 'stg_orders',\n  incrementalStrategy: 'merge',\n  updateFrequency: 'hourly',\n  dataVolume: 'large',\n  uniqueKey: ['order_id'],\n  partitionBy: { field: 'order_date', granularity: 'day' },\n  backfillRequired: true\n});",
    "usesAgents": [
      "incremental-strategy-architect",
      "unique-key-engineer",
      "filter-logic-engineer",
      "partitioning-architect",
      "clustering-engineer",
      "model-developer",
      "test-engineer",
      "backfill-architect",
      "performance-optimizer",
      "monitoring-engineer",
      "validation-specialist",
      "documentation-writer"
    ]
  },
  "outgoingEdges": [
    {
      "from": "lib-process:data-engineering-analytics--incremental-model",
      "to": "domain:data-engineering",
      "kind": "lib_applies_to_domain",
      "attributes": {
        "weight": 1
      }
    },
    {
      "from": "lib-process:data-engineering-analytics--incremental-model",
      "to": "workflow:data-pipeline-deployment",
      "kind": "lib_implements_workflow",
      "attributes": {
        "weight": 1
      }
    },
    {
      "from": "lib-process:data-engineering-analytics--incremental-model",
      "to": "specialization:data-engineering-analytics",
      "kind": "lib_belongs_to_specialization",
      "attributes": {
        "weight": 0.9
      }
    },
    {
      "from": "lib-process:data-engineering-analytics--incremental-model",
      "to": "lib-agent:shared--test-engineer",
      "kind": "uses_agent",
      "attributes": {
        "weight": 0.8
      }
    },
    {
      "from": "lib-process:data-engineering-analytics--incremental-model",
      "to": "lib-agent:shared--documentation-writer",
      "kind": "uses_agent",
      "attributes": {
        "weight": 0.8
      }
    }
  ],
  "incomingEdges": []
}