Export datasets to cloud storage destinations
- This functionality is available to customers who have purchased the Real-Time CDP Prime or Ultimate package, ÃÛ¶¹ÊÓƵ Journey Optimizer, or Customer Journey Analytics. Contact your ÃÛ¶¹ÊÓƵ representative for more information.
This article explains the workflow required to export datasets from ÃÛ¶¹ÊÓƵ Experience Platform to your preferred cloud storage location, such as Amazon S3, SFTP locations, or Google Cloud Storage by using the Experience Platform UI.
You can also use the Experience Platform APIs to export datasets. Read the export datasets API tutorial for more information.
Datasets available for exporting datasets-to-export
The datasets that you can export vary based on the Experience Platform application (Real-Time CDP, ÃÛ¶¹ÊÓƵ Journey Optimizer), the tier (Prime or Ultimate), and any add-ons that you purchased (for example: Data Distiller).
Use the table below to understand which dataset types you can export depending on your application, product tier, and any add-ons purchased:
- Profile and Experience Event datasets created in the Experience Platform UI after ingesting or collecting data through Sources, Web SDK, Mobile SDK, Analytics Data Connector, and Audience Manager.
- System-generated Profile Snapshot dataset.
Video tutorial video-tutorial
Watch the video below for an end-to-end explanation of the workflow described on this page, benefits of using the export dataset functionality, and some suggested use cases.
Supported destinations supported-destinations
Currently, you can export datasets to the cloud storage destinations highlighted in the screenshot and listed below.
When to activate audiences or export datasets when-to-activate-audiences-or-activate-datasets
Some file-based destinations in the Experience Platform catalog support both audience activation and dataset export.
- Consider activating audiences when you want your data structured into profiles grouped by audience interests or qualifications.
- Alternatively, consider dataset exports when you are looking to export raw datasets, which are not grouped or structured by audience interests or qualifications. You could use this data for reporting, data science workflows, and many other use cases. For example, as an administrator, data engineer, or analyst, you can export data from Experience Platform to synchronize with your data warehouse, use in BI analysis tools, external cloud ML tools, or store in your system for long-term storage needs.
This document contains all the information necessary to export datasets. If you want to activate audiences to cloud storage or email marketing destinations, read Activate audience data to batch profile export destinations.
Prerequisites prerequisites
To export datasets to cloud storage destinations, you must have successfully connected to a destination. If you haven’t done so already, go to the destinations catalog, browse the supported destinations, and configure the destination that you want to use.
Required permissions permissions
To export datasets, you need the View Destinations, View Datasets, and Manage and Activate Dataset Destinations access control permissions. Read the access control overview or contact your product administrator to obtain the required permissions.
To ensure that you have the necessary permissions to export datasets and that the destination supports exporting datasets, browse the destinations catalog. If a destination has an Activate or an Export datasets control, then you have the appropriate permissions.
Select your destination select-destination
Follow the instructions to select a destination where you can export your datasets:
-
Go to Connections > Destinations, and select the Catalog tab.
-
Select Activate or Export datasets on the card corresponding to the destination that you want to export datasets to.
-
Select Data type Datasets and select the destination connection that you want to export datasets to, then select Next.
- The Select datasets view appears. Proceed to the next section to select your datasets for export.
Select your datasets select-datasets
Use the check boxes to the left of the dataset names to select the datasets that you want to export to the destination, then select Next.
Schedule dataset export scheduling
Use the Scheduling step to:
- Set a start date and an end date, as well as an export cadence for your dataset exports.
- Configure if the exported dataset files should export the complete membership of the dataset or just incremental changes to the membership on each export occurrence.
- Customize the folder path in your storage location where datasets should be exported. Read more about how to edit the export folder path.
Use the Edit schedule control on the page to edit the export cadence of exports, as well as to select whether to export full or incremental files.
The Export incremental files option is selected by default. This triggers an export of one or multiple files representing a full snapshot of the dataset. Subsequent files are incremental additions to the dataset since the previous export. You can also select Export full files. In this case, select the frequency Once for a one-time full export of the dataset.
-
Use the Frequency selector to select the export frequency:
- Daily: Schedule incremental file exports once a day, every day, at the time you specify.
- Hourly: Schedule incremental file exports every 3, 6, 8, or 12 hours.
-
Use the Time selector to choose the time of day, in UTC format, when the export should take place.
-
Use the Date selector to choose the interval when the export should take place.
-
Select Save to save the schedule and proceed to the Review step.
Edit folder path edit-folder-path
Select Edit folder path to customize the folder structure in your storage location where exported datasets are deposited.
You can use several available macros to customize a desired folder name. Double-click a macro to add it to the folder path and use /
between the macros to separate the folders.
After selecting the desired macros, you can see a preview of the folder structure that will be created in your storage location. The first level in the folder structure represents the Folder path that you indicated when you connected to the destination to export datasets.
Review review
On the Review page, you can see a summary of your selection. Select Cancel to break up the flow, Back to modify your settings, or Finish to confirm your selection and start exporting datasets to the destination.
Verify successful dataset export verify
When exporting datasets, Experience Platform creates one or multiple .json
or .parquet
files in the storage location that you provided. Expect new files to be deposited in your storage location according to the export schedule you provided.
Experience Platform creates a folder structure in the storage location you specified, where it deposits the exported dataset files. The default folder export pattern is shown below, but you can customize the folder structure with your preferred macros.
folder-name-you-provided
- represents the Folder path that you indicated when you connected to the destination to export datasets.folder-name-you-provided/datasetID/exportTime=YYYYMMDDHHMM
The default file name is randomly generated and ensures that exported file names are unique.
Sample dataset files sample-files
The presence of these files in your storage location is confirmation of a successful export. To understand how the exported files are structured, you can download a sample .parquet file or .json file.
Compressed dataset files compressed-dataset-files
In the connect to destination workflow, you can select the exported dataset files to be compressed, as shown below:
Note the difference in file format between the two file types, when compressed:
- When exporting compressed JSON files, the exported file format is
json.gz
. The format of the exported JSON is NDJSON, which is the standard interchange format in the big data ecosystem. ÃÛ¶¹ÊÓƵ recommends using an NDJSON-compatible client to read the exported files. - When exporting compressed parquet files, the exported file format is
gz.parquet
Exports to JSON files are supported in a compressed mode only. Exports to Parquet files are supported in a compressed and uncompressed mode.
Remove datasets from destinations remove-dataset
To remove datasets from an existing dataflow, follow the steps below:
-
Log in to the and select Destinations from the left navigation bar. Select Browse from the top header to view your existing destination dataflows.
note tip TIP Select the filter icon on the top left to launch the sort panel. The sort panel provides a list of all your destinations. You can select more than one destination from the list to see a filtered selection of dataflows associated with the selected destination. -
From the Activation data column, select the datasets control to view all datasets mapped to this export dataflow.
-
The Activation data page for the destination appears. Use the checkboxes on the left side of the dataset list to select the datasets which you want to remove, then select Remove datasets in the right rail to trigger the remove dataset confirmation dialog.
-
In the confirmation dialog, select Remove to immediately remove the dataset from exports to the destination.
Dataset export entitlements licensing-entitlement
Refer to the product description documents to understand how much data you are entitled to export for each Experience Platform application, per year. For example, you can view the Real-Time CDP Product Description .
Note that the data export entitlements for different applications are not additive. For example, this means that if you purchase Real-Time CDP Ultimate and ÃÛ¶¹ÊÓƵ Journey Optimizer Ultimate, the profile export entitlement will be the larger of the two entitlements, as per the product descriptions. Your volume entitlements are calculated by taking your total number of licensed profiles and multiplying by 500 KB for Real-Time CDP Prime or 700 KB for Real-Time CDP Ultimate to determine how much volume of data you are entitled to.
On the other hand, if you purchased add-ons such as Data Distiller, the data export limit that you are entitled to represents the sum of the product tier and the add-on.
You can view and track your profile exports against your contractual limits in the license usage dashboard.
Known limitations known-limitations
Keep in mind the following limitations for the general availability release of dataset exports:
- Experience Platform may export multiple files even for small datasets. Dataset export is designed for system-to-system integration and optimized for performance, hence the number of exported files is not customizable.
- Exported file names are currently not customizable.
- Datasets created via API are currently not available for export.
- The UI does not currently block you from deleting a dataset that is being exported to a destination. Do not delete any datasets that are being exported to destinations. Remove the dataset from a destination dataflow before deleting it.
- Monitoring metrics for dataset exports are currently mixed with numbers for profile exports so they do not reflect the true export numbers.
- Data with a timestamp older than 365 days is excluded from dataset exports. For more information, view the guardrails for scheduled dataset exports
Frequently Asked Questions faq
Can we generate a file without a folder if we just save at /
as the folder path? Also, if we don’t require a folder path, how will files with duplicate names be generated in a folder or location?
/
for exporting files for all datasets in the same folder. ÃÛ¶¹ÊÓƵ does not recommend this for destinations exporting multiple datasets, as system-generated filenames belonging to different datasets will be mixed in the same folder.Can you route the manifest file to one folder and data files into another folder?
Can we control the sequencing or timing of file delivery?
What formats are available for the manifest file?
Is there API availability for the manifest file?
Can we add additional details to the manifest file (i.e., record count)? If so, how?
flowRun
entity (queryable via API). Read more in destinations monitoring.How are data files split? How many records per file?
Can we set a threshold (number of records per file)?
How do we resend a data set in the event that the initial send is bad?