Name: IdentitySync - SAP Customer Data Cloud
Uploaded: 2020-3-3
Duration: 365 s
Description: In this video, we will demonstrate IdentitySync, SAP Customer Data Cloud's solution for transferring data between platforms.

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<div><div><div><div><div>In this video, we will demonstrate IdentitySync, SAP Customer Data Cloud's solution for transferring data between platforms.<div><br></div></div></div></div></div></div>

IdentitySync - SAP Customer Data Cloud

In this video, we'll demonstrate IdentitySync  SAP Customer Data Cloud's solution for transferring data between platforms. You will learn what is Identity Sync? How to Create Identity Sync dataflows for exporting and importing user data Identity Sync terminologies, followed by an in-depth demo. With Identity Sync, You can read data from a wide range of platforms such as storage, marketing, or data management solutions, or from the CDC database. You can transform that data in many different ways and upload it to the target platform, which can be CDC or a third-party platform. So, it's the go-to place for integrating your user data into third party systems. In addition, it's used for migrating users between two different CDC sites and for importing user data into  CDC. Before we start the demo, let's review some of the basic terms we use when we discuss identity sync. Each identity sync job runs a dataflow. The building blocks of the dataflow are dedicated components. A component is a preconfigured unit that is used to perform a specific data integration operation. The components include readers, writers, transformers, deleters, and look-ups. Each component is responsible for performing a single task, such as extracting accounts from SAP Customer Data Cloud based on specific parameters, changing field names, creating a CSV file, uploading a file to FTP and writing data directly to a target platform or sending it to a generic API endpoint. Components can be added to the data flow as well as removed or changed as needed. The information you need for working with each component is documented in our component repository page in the developer's guide. Let's get started. We're going to demo importing ten new accounts into a new side we created in SAP Customer Data Cloud, Let's open Identity Access on the console where all our users are displayed. As you can see, there are no users yet. We have a JSON file prepared with ten users. The users must have a UID field which will identify them in the CDC database. If they don't, we could add a step in identity sync that generates random UIDs. Now back in the console on the left-hand menu, open Identity Sync dataflows. Create a new data flow and select Gigya with SFTP. We're going to import full accounts from SFTP and press continue. A full dataflow is created and opens automatically in the what you see is what you get editor. The first step is to read the file from SFTP. Double-click on the step to enter the necessary parameters, in this case, the SFTP credentials.  Next, the import job parses the file so that the Customer Data Cloud service can read it as a JSON. You can see that this step accepts the file as an input, whereas the next steps, accept a record. In the next step, we inject a job ID to each of the imported records. This is useful when there is a problem with the import, so we can check all the records with the same job ID and fix them if there's an issue. The next step is the actual import. There are no mandatory parameters here. Hover over the question mark of the import policy parameter to read the explanation for it. After the import, we have additional steps that allow us to handle an error. The red dotted arrow indicates that this is an error path. Format the problematic records into a JSON file and save that file to SFTP. Again, you need to enter your SFTP hostname and credentials here.  Once we're finished editing the flow, hit Save and Close. Now let's open the Actions menu. We can run a test to see if our flow is defined correctly. But instead, let's open the scheduler. Here we can create a onetime or reoccurring schedule for the Dataflow. Give your schedule a name, select the runtime and whether it runs once or at scheduled intervals. You can choose the log level: choose error, and only error logs will be displayed and the job trace, choose info an info an error logs will be displayed in the trace, or choose debug where besides info an error logs. Each record will be logged between every two steps. That should be used only if the dataflow is not working as expected and is limited to a batch of three records. In addition, you can limit the job to a specified number of records, and email addresses to which feedback of job success or failure will be sent. Back to the scheduling dashboard, you can refresh the dashboard and see that since we chose to run once, the schedule disappears once the job is completed. When you select back to dataflows, you can see the last successful run of this job. Navigate to the job status page to see the details of the job's execution. There are four statuses that may be shown for a job: succeeded, completed with errors, failed and stopped, which means someone stop the dataflow mid run. Click on the information icon to view further details.  So our job completed successfully and we should now be able to see the new records in identity access. When you open the user profile, you can see in the custom fields that the job ID was added to this user. We can also open our email and see that a success notification was sent for this job.  This concludes our demo of using Identity Sync to import accounts into Customer Data Cloud. Thank you for watching.