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Transcript

In this video, I’ll show you how to export an Experience Platform dataset to a cloud storage destination, as well as review the benefits and use cases for this feature. These are the topics I’ll cover. I’ll give you a moment to finish reviewing this slide. Using cloud storage destinations, an easy-to-use interface and workflow is available to export event data and CRM records from Experience Platform. The core tenants of data governance and supporting an open framework apply. Data labels are enforced for dataset exports, as is the case for other types of destination workflows. Our framework supports interoperability between Experience Platform and public clouds to support use cases involving data stored in the data lake to be used in external systems. Real-time CDP and Journey Optimizer customers have several primary use cases for exporting Experience Platform datasets and using a straightforward method for doing this from the destination’s catalog. Datasets can be exported for use in external machine learning and business intelligence tools to support analytical use cases, such as reporting and informing better audience creation. Log data can be exported for the purpose of monitoring the health and performance of email marketing campaigns. These are the cloud storage destinations that can be used for dataset exports. If you don’t see the dataset option in the export workflow, check your user permissions. You’ll need the View Destinations and Manage and Activate Dataset Destinations permissions. Additionally, you’ll want to ensure you have the proper data management permissions for datasets, namely View Datasets. Next, I’ll demo configuring a cloud storage account I’ll use for dataset exports. I’m logged in to Experience Platform. I’ll select Destinations below Connections in the left navigation panel. Once the Destinations catalog displays, I’ll scroll to the Categories section and select Cloud Storage. I’ll be working with an Amazon S3 account. While you may have existing Amazon S3 connections, you’ll need to create a new connection for exporting datasets. In the top right corner of the Amazon S3 destination card, I’ll select the Dataset icon. This opens a new panel on the right. I’ll select the Configure New Destination link. In the Configure New Destination screen, I’ll select an existing account. From the Select Destination account modal, I’ll choose one from the list and then I’ll click on Select in the upper right corner. Under Destination Details, I’ll select Datasets. Notice the destination also supports prospects and audiences. Then I’ll fill in the Name, Description, Bucket Name, and Folder Path fields. The last two fields specify which area and path of the S3 account the dataset files will be stored. For the Field Type field, I have two field options, JSON and Parquet. I’ll choose JSON. Towards the bottom, I can also choose a compression format, which I’ll do now. The choice is relative to the file type selected above. Then I can choose any alerts I wish to receive for this export. When I’m done, I’ll select Next in the top right. This step of the Configure New Destination is prompting me to select the marketing action appropriate for this connection. I’ll choose Data Export from the list and then Create in the top right. Now that I’ve set up the new connection for the dataset export in my Amazon S3 account, I’ll demonstrate the workflow to export one. I’ll choose the Activate command for Amazon S3. I’ll select Datasets as the data type. This shows me the new connection I just created. I’ll choose this and select Next in the upper right corner. The Select Dataset step in the workflow lets me view and choose the dataset I want to export. Notice some of the Journey Optimizer datasets in the list as well. Once I choose the dataset, I’ll select Next in the upper right corner. On the Scheduling step, the File Export option is set to Export Incremental Files. The first exported incremental file includes all existing data in that dataset, functioning as a backfill. Next I can choose a frequency setting. My choices are daily and hourly. Hourly has several different presets associated with it. I could customize the start date if I needed to do that as well. Now I’ll click Next in the upper corner. This takes me to a review step where I can verify my settings. Once everything looks good, I’ll select Finish in the upper right corner. That’s it! It’s very straightforward as you can see. After this, you would connect to the S3 bucket to confirm you see your files there. An export time is appended to the end of each file. This concludes the Dataset Export video. Hopefully you’ll be able to export datasets using a cloud storage destination. Thanks and good luck!