Delete dataflows in the UI
- Topics:
- Sources
CREATED FOR:
- Developer
The Sources workspace allows you to delete existing batch and streaming dataflows that contain errors or have become obsolete.
This tutorial provides steps for deleting dataflows using the Sources workspace.
Getting started
This tutorial requires a working understanding of the following components of Adobe Experience Platform:
- Sources: Experience Platform allows data to be ingested from various sources while providing you with the ability to structure, label, and enhance incoming data using Experience Platform services.
- Sandboxes: Experience Platform provides virtual sandboxes which partition a single Experience Platform instance into separate virtual environments to help develop and evolve digital experience applications.
Delete dataflows
In the Experience Platform UI, select Sources from the left navigation to access the Sources workspace, and then select Dataflows from the top header.
The Dataflows page appears. On this page is a list of viewable dataflows, including information about their target dataset, source, account name, and date of creation.
Select the filter icon (
The sort panel provides a list of all sources. You can select more than one source from the list to access a filtered selection of dataflows associated with the particular sources you selected.
Select the source you wish to work with to see a list of its existing dataflows. Once you have identified the dataflow you want to delete, select the ellipses (...
) beside the dataflow name.
A dropdown menu appears, providing you with options to edit your dataflow’s schedule, disable the dataflow, or delete it entirely.
Select Delete to delete the dataflow.
A final confirmation dialog box appears. Select Delete to complete the process.
After a few moments, a confirmation box appears on the bottom of the screen to confirm a successful deletion.
Next steps
By following this tutorial, you have successfully used the Sources workspace to delete an existing dataflow.
See the tutorial on deleting dataflows using the Flow Service API for steps on how to perform these operations programmatically using API calls.
Experience Platform
- Sources overview
- Available source connectors
- Adobe applications
- Advertising
- Analytics
- Cloud storage
- Amazon Kinesis connector
- Amazon S3 connector
- Apache HDFS connector
- Azure Data Lake Storage Gen2 connector
- Azure Blob connector
- Azure Event Hubs connector
- Azure File Storage connector
- Data Landing Zone
- FTP connector
- Google Cloud Storage connector
- Google PubSub
- Oracle Object Storage
- SFTP connector
- Amazon S3 and Azure Blob connector
- Consent & Preferences
- CRM
- Customer success
- Databases
- Amazon Redshift connector
- Apache Hive on Azure HDInsights connector
- Apache Spark on Azure HDInsights connector
- Azure Databricks connector
- Azure Data Explorer connector
- Azure Synapse Analytics connector
- Azure Table Storage connector
- Google BigQuery connector
- GreenPlum connector
- HP Vertica connector
- IBM DB2 connector
- MariaDB connector
- Microsoft SQL Server connector
- MySQL connector
- Oracle connector
- PostgreSQL connector
- Snowflake Streaming connector
- Snowflake connector
- Teradata Vantage connector
- Data & identity partner
- eCommerce
- Local system
- Marketing automation
- Payments
- Protocols
- Streaming
- API tutorials
- Create a base connection
- Explore data
- Collect data
- On-demand ingestion
- Filter data at the source level
- Monitor dataflows
- Update accounts
- Update dataflows
- Retry failed dataflow runs
- Delete accounts
- Delete dataflows
- Ingest encrypted data
- Save a dataflow as a draft
- Apply access labels to a dataflow
- UI tutorials
- Create a source connection
- Adobe applications
- Advertising
- Analytics
- Cloud storage
- Consent & Preferences
- CRM
- Customer Success
- Databases
- Amazon Redshift
- Apache Hive on Azure HDInsights
- Apache Spark on Azure HDInsights
- Azure Databricks
- Azure Data Explorer
- Azure Synapse Analytics
- Azure Table Storage
- Google Big Query
- GreenPlum
- HP Vertica
- IBM DB2
- MariaDB
- Microsoft SQL Server
- MySQL
- Oracle
- PostgreSQL
- Snowflake
- Snowflake Streaming
- Teradata Vantage
- Data & identity partner
- eCommerce
- Local system
- Marketing automation
- Payments
- Protocols
- Streaming
- Configure a dataflow
- Advertising connection dataflow
- Analytics connection dataflow
- Batch cloud storage connection dataflow
- Streaming cloud storage connection dataflow
- Consent & Preferences connection dataflow
- CRM connection dataflow
- Customer success connection dataflow
- Database connection dataflow
- Ecommerce connection dataflow
- Marketing automation connection dataflow
- Payment connection dataflow
- Protocol connection dataflow
- Create a sources dataflow using templates in the UI
- Ingest encrypted data
- On-demand ingestion
- Monitor batch dataflows
- Monitor streaming dataflows
- Update accounts
- Update dataflows
- Delete accounts
- Delete dataflows
- Subscribe to sources alerts
- Save a dataflow as a draft
- Apply access labels to a dataflow
- Create a source connection
- Self-Serve Sources (Batch SDK)
- Overview
- Configure your connection specification
- Self-Serve Sources (Batch SDK) API guide
- Documentation guide
- Streaming SDK
- Get started with Self-Serve Sources (Streaming SDK)
- Create a connection specification for a streaming source
- Update a connection specification for a streaming source
- Update the streaming flow specification
- Test and submit your connection specification for verification
- Document your source (Streaming SDK)
- Documentation self-service API streaming template
- Documentation self-service UI streaming template
- Error messages
- Flow run notifications
- IP address allow list
- Frequently asked questions
- API reference
- Experience Platform release notes