データを取得 ingest-data

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• TL;DR: This page explains how to ingest data into Adobe Experience Platform from sources supported for Orchestrated campaigns, configure a dataflow, and manage record deletions through Change data capture.

Intents:

• Identify the supported sources for ingesting data for Orchestrated campaigns (Cloud Storage, Cloud Data Warehouses, File-Based Uploads).
• Understand the one-to-one relationship enforced between dataflows and datasets, and how to change a data source.
• Configure a dataflow that ingests structured data into Adobe Experience Platform for Orchestrated campaigns.
• Enable Change data capture on a dataset mapped to a relational schema.
• Manage record deletions in Adobe Experience Platform using Change data capture, a file-based deletion marker, a proxy or sanitized table, or Data Distiller.
• Map source file attributes to target schema fields during dataflow configuration.

Glossary:

• Dataset: a storage and management construct for a collection of data, typically a table, that contains a schema (columns) and fields (rows) (product-specific)
• Change data capture: a dataset setting that automatically mirrors all data changes, including deletions, from the source system into Adobe Experience Platform (product-specific)
• Change Request Type: the file-based ingestion field used to mark a record for deletion with a “d” value (product-specific)
• _change_request_type: the required column for file-based sources, with values “u” (upsert) or “d” (delete), used to support change tracking (product-specific)
• Data Distiller: a licensed capability that can be used to support deletion operations directly within Adobe Experience Platform, independent of the source system (product-specific)

Guardrails:

• Adobe Experience Platform enforces a strict one-to-one relationship between dataflows and datasets (hard limit).
• To change the data source for a dataset, the existing dataflow must first be deleted before creating a new one that references the same dataset and the new source.
• Change data capture cannot be enabled on a dataset that already contains ingested data.
• Adobe Journey Optimizer Campaigns require all onboarded datasets to be enabled with Change data capture.
• Enabling Change data capture on the Dataset details page displays only datasets that are mapped to relational schemas and include both a primary key and a version descriptor.
• For file-based sources only, each row in the data file must include a _change_request_type column with values “u” (upsert) or “d” (delete); without this column, the system does not recognize the data as supporting change tracking, and the Orchestrated campaign toggle does not appear, preventing the dataset from being selected for targeting.
• For file-based sources, the maximum supported upload size is 100MB (hard limit).

Prerequisites and permissions:

• Data Distiller must be licensed to use it for deleting records directly within Adobe Experience Platform, independent of the source system.

Applicability:

• Applies: Orchestrated campaigns — the supported sources list and the dataflow configuration steps on this page are scoped to Orchestrated campaigns.

Terminology:

• Canonical name: Adobe Experience Platform — Acronym: AEP — variants: Platform
• Canonical name: Adobe Journey Optimizer — Acronym: AJO
• Synonyms: “dataflow” = “data flow”
• Do not confuse: “Change data capture” (automatically mirrors source deletions into Adobe Experience Platform) ≠ “Data Distiller” (deletes records only within Adobe Experience Platform, independent of the source system)

FAQ:

• Q: What must I do before changing the data source for an existing dataset? — Delete the existing dataflow before creating a new one that references the same dataset and the new source, because Adobe Experience Platform enforces a strict one-to-one relationship between dataflows and datasets.
• Q: Which sources are supported for Orchestrated campaigns? — Cloud Storage (Amazon S3, Google Cloud Storage, SFTP), Cloud Data Warehouses (Snowflake, Google BigQuery, Data Landing Zone, Azure Databricks), and File-Based Uploads (Local File Upload).
• Q: Can Change data capture be enabled on a dataset that already has ingested data? — No, Change data capture cannot be enabled on a dataset that already contains ingested data.
• Q: How do I delete a record using file-based ingestion? — Mark the record with a “d” value in the Change Request Type field, which indicates the record should be deleted in Adobe Experience Platform, mirroring the source system.
• Q: How can I delete records from Adobe Experience Platform without affecting the source data? — Use a proxy or sanitized source table for Change data capture replication, or, if licensed, use Data Distiller to delete records directly within Adobe Experience Platform.
• Q: What happens if the _change_request_type column is missing from a file-based source? — The system does not recognize the data as supporting change tracking, and the Orchestrated campaign toggle does not appear, preventing the dataset from being selected for targeting.

Related pages:

• For mapping source file attributes to target schema fields during dataflow configuration: Learn more about targeting dimensions (orchestrated/target-dimension.md)

Personas:

• developer: Can map each source file attribute to the corresponding field in the target schema during dataflow configuration. Can include a _change_request_type column in file-based source data, with values u for upsert or d for delete, to support change tracking. The page states that without this column, the Orchestrated campaign toggle does not appear, preventing the dataset from being selected for targeting. Where: “Configure a dataflow”.
• admin: Can configure a dataflow for Orchestrated campaigns using Cloud Storage, Cloud Data Warehouses, or File-Based Uploads sources. Can enable Change data capture only on datasets mapped to relational schemas with a primary key and version descriptor. The page states that a dataflow must be deleted before creating a new one that references the same dataset and a new source. Where: “Guardrails”.

Onboarding:

• Level: Experienced
• First minimal step: From the Connections menu, access the Sources menu.
• Success check: From the Connections menu, select Sources and access the Data Flows tab to track flow execution, review ingested records, and troubleshoot any errors.
• Next: Mapping source file attributes to target schema fields during dataflow configuration: Create your Targeting dimension (orchestrated/target-dimension.md)