Creating your first data flow (ETL - Extract, Transform, Load) in SAP Data Intelligence (formerly known as SAP DataSphere) involves a series of steps to extract data from a source, transform it, and then load it into a target destination. Here's a concise overview of the process:

1. Access SAP Data Intelligence: Log in to your SAP Data Intelligence environment and navigate to the appropriate workspace or project where you want to create your data flow.

2. Create a Pipeline: Start by creating a new pipeline. Pipelines in SAP Data Intelligence define the sequence of operations for data processing.

3. Add Source Node: Add a source node to your pipeline. This node represents the data source you want to extract data from. It could be a database, file system, API, etc.

4. Configure Source Node: Configure the source node with the necessary connection details, credentials, and other parameters specific to your data source.

5. Add Transformation Nodes: Add transformation nodes to your pipeline. These nodes perform data transformations like filtering, aggregation, data type conversions, etc. You can add multiple transformation nodes in sequence as needed.

6. Configure Transformation Nodes: Configure each transformation node with the appropriate settings and transformation logic based on your data processing requirements.

7. Add Target Node: Add a target node to your pipeline. This node represents the destination where you want to load your transformed data. It could be another database, a file, or any supported target.

8. Configure Target Node: Configure the target node with the necessary connection details, credentials, and other parameters specific to your target destination.

9. Connect Nodes: Establish connections between the nodes in your pipeline. The output of one node should be connected to the input of the next node in the sequence.

10. Define Data Flow Path: Define the data flow path through your pipeline, specifying how data should move from the source through the transformations and finally to the target.

11. Save and Execute: Save your pipeline configuration and execute it. This will trigger the ETL process, where data is extracted, transformed, and loaded according to your defined flow.

12. Monitor and Debug: Monitor the execution of your pipeline and use debugging tools if necessary to troubleshoot any issues in your data flow.

13. Validate Results: Once the pipeline execution is complete, validate that the data has been successfully transformed and loaded into the target destination as expected.

14. Save and Publish: If you're satisfied with your data flow, save and publish your pipeline. This ensures that your ETL process can be executed reliably in the future.

15. This video starts by introducing the concept of data flows and their importance in data processing. You'll learn how to access SAP DataSphere and navigate its user-friendly interface. We will guides you through defining data sources, applying data transformations, and configuring target destinations.