On this page: Learn how to ingest data into Adobe Experience Platform from supported sources and configure a dataflow for your Orchestrated campaigns.
Adobe Experience Platform allows data to be ingested from external sources while providing you with the ability to structure, label, and enhance incoming data using Experience Platform services. You can ingest data from a variety of sources such as Adobe applications, cloud-based storages, databases, and many others.
A dataset is a storage and management construct for a collection of data, typically a table, that contains a schema (columns) and fields (rows). Data that is successfully ingested into Experience Platform is stored within the data lake as datasets.
Supported sources for orchestrated campaigns supported
The following Dources are supported for use with Orchestrated campaigns:
Guidelines for relational Schema data hygiene cdc
For datasets enabled with Change data capture, all data changes including deletions, are automatically mirrored from the source system into Adobe Experience Platform. You cannot enable Change data capture on a dataset that already contains ingested data.
Since Adobe Journey Optimizer Campaigns require all onboarded datasets to be enabled with Change data capture, it is the customer’s responsibility to manage deletions at the source. Any record deleted from the source system will automatically be removed from the corresponding dataset in Adobe Experience Platform.
To delete records via file-based ingestion, the customer’s data file should mark the record using a d value in the Change Request Type field. This indicates that the record should be deleted in Adobe Experience Platform, mirroring the source system.
If customer wants to delete records only from Adobe Experience Platform without affecting the original source data, the following options are available:
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Proxy or Sanitized Table for Change data capture Replication
Customer can create a proxy or sanitized source table to control which records are replicated into Adobe Experience Platform. Deletions can then be managed selectively from this intermediary table.
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Deletion via Data Distiller
If licensed, Data Distiller can be used to support deletion operations directly within Adobe Experience Platform, independent of the source system.
Configure a dataflow
This example demonstrates how to configure a data flow that ingests structured data into Adobe Experience Platform. The configured data flow supports automated, scheduled ingestion and enables real-time updates.
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From the Connections menu, access the Sources menu.
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Choose your source depending on the Supported Sources for Orchestrated campaigns.
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Connect your Cloud Storage or Google Cloud Storage account if you chose cloud based sources.
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Choose the data to ingest into Adobe Experience Platform.
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From the Dataset details page, check Enable Change data capture to display only datasets that are mapped to relational schemas and include both a primary key and a version descriptor.
Learn more on guidelines for relational Schemas data hygiene
note important IMPORTANT For file-based sources only, each row in the data file must include a _change_request_typecolumn with valuesu(upsert) ord(delete). Without this column, the system will not recognize the data as supporting change tracking, and the Orchestrated campaign toggle will not appear, preventing the dataset from being selected for targeting.
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Select your previously created Dataset and click Next.
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If you are using a file-based sources only, from the Select data window, upload your local files and preview their structure and contents.
Note that the maximum supported size is 100MB.
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In the Mapping window, verify that each source file attribute is correctly mapped with the corresponding fields in the target schema. Learn more about targeting dimensions.
Click Next once done.
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Configure the data flow Schedule based on your desired frequency.
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Click Finish to create the data flow. It will execute automatically according to the defined schedule.
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From the Connections menu, select Sources and access the Data Flows tab to track flow execution, review ingested records, and troubleshoot any errors.
This section contains structured knowledge intended to support interpretation, retrieval, and question answering related to this topic.
For complete understanding, this information should be combined with the documentation on this page. Neither source is intended to stand alone; the page describes the feature, while this section provides additional context that helps disambiguate terminology, intent, applicability, and constraints.
- 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)