Integrations Inventory and Attributes - Data and Information attributes for the Integrations Inventory

Integrations Inventory and Attributes

Data and Information attributes for the Integrations Inventory

Data and Information attributes capture the specific data objects, formats, and transformations involved in this Integration — connecting the integration map to the enterprise data architecture.

Attribute Name	Maturity	Description and Notes
Source Data Object	Walk	Description — The specific entity, table, schema, object, file, queue, or topic in the source system that provides the data for this integration. Benefit(s) — Enables precise data lineage tracing. When a source system is decommissioned or its schema changes, Source Data Object identifies exactly which integrations are affected and what must be remapped. Source — Manual. Examples — CUSTOMERS table in CRM_PROD database, /orders/confirmed endpoint, customer-events Kafka topic, VENDOR_INVOICES_OUT SFTP directory
Target Data Object	Walk	Description — The specific entity, table, schema, object, file, queue, or topic in the target system that receives the data from this integration. Benefit(s) — Completes the data lineage picture from source to target. Enables impact analysis when a target system’s receiving schema changes. Source — Manual. Examples — CUSTOMER_MASTER table in ERP_PROD database, /intake/customers endpoint, customer-profiles S3 bucket, PAYMENT_IN queue
Transformation Required	Walk	Description — Whether data is transformed between source format and target format as part of this integration, and where the transformation logic resides. Benefit(s) — Surfaces hidden complexity in the integration. A transformation that lives in undocumented custom code is a key person dependency and a fragility risk. Explicit transformation documentation is the first step to reducing that risk. Source — Manual. Examples — Yes — transformation logic in Informatica mapping; Yes — transformation in Python script; Yes — field mapping in MuleSoft DataWeave; No transformation — pass-through

Attribute Name

Maturity

Description and Notes

Source Data Object

Walk

Description — The specific entity, table, schema, object, file, queue, or topic in the source system that provides the data for this integration.

Benefit(s) — Enables precise data lineage tracing. When a source system is decommissioned or its schema changes, Source Data Object identifies exactly which integrations are affected and what must be remapped.

Source — Manual.

Examples — CUSTOMERS table in CRM_PROD database, /orders/confirmed endpoint, customer-events Kafka topic, VENDOR_INVOICES_OUT SFTP directory

Target Data Object

Walk

Description — The specific entity, table, schema, object, file, queue, or topic in the target system that receives the data from this integration.

Benefit(s) — Completes the data lineage picture from source to target. Enables impact analysis when a target system’s receiving schema changes.

Source — Manual.

Examples — CUSTOMER_MASTER table in ERP_PROD database, /intake/customers endpoint, customer-profiles S3 bucket, PAYMENT_IN queue

Transformation Required

Walk

Description — Whether data is transformed between source format and target format as part of this integration, and where the transformation logic resides.

Benefit(s) — Surfaces hidden complexity in the integration. A transformation that lives in undocumented custom code is a key person dependency and a fragility risk. Explicit transformation documentation is the first step to reducing that risk.

Source — Manual.

Examples — Yes — transformation logic in Informatica mapping; Yes — transformation in Python script; Yes — field mapping in MuleSoft DataWeave; No transformation — pass-through

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