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Data quality in Adobe Experience Platform

Adobe Experience Platform provides well-defined guarantees for completeness, accuracy, and consistency for any data uploaded through either batch or streaming ingestion. The following document provides a summary of the supported checks and validation behaviors for batch and streaming ingestion in Experience Platform.

Supported checks

 
Batch Ingestion
Streaming Ingestion
Data type check
Yes
Yes
Enum check
Yes
Yes
Range check (min, max)
Yes
Yes
Required field check
Yes
Yes
Pattern check
No
Yes
Format check
No
Yes

Supported validation behaviors

Both batch and streaming ingestion prevent failed data from going downstream by moving bad data for retrieval and analysis in Data Lake. Data ingestion provides the following validations for batch and streaming ingestion.

Batch ingestion

The following validations are done for batch ingestion:
Validation area
Description
Schema
Ensures that the schema is not empty and contains a reference to the union schema, as follows: "meta:immutableTags": ["union"]
identityField
Ensures that all valid identity descriptors are defined.
createdUser
Ensures that the user who ingested the batch is allowed to ingest the batch.

Streaming ingestion

The following validations are done for streaming ingestion:
Validation area
Description
Schema
Ensures that the schema is not empty and contains a reference to the union schema, as follows: "meta:immutableTags": ["union"]
identityField
Ensures that all valid identity descriptors are defined.
JSON
Ensures that the JSON is valid.
IMS Organization
Ensures that the IMS Organization that is listed is a valid organization.
Source name
Ensures that the name of the data source is specified.
Dataset
Ensures that the dataset is specified, enabled, and has not been removed.
Header
Ensures that the header is specified and is valid.
More information about how Platform monitors and validates data can be found in the monitoring data flows documentation .