To achieve and maintain clean core data quality in an SAP S/4HANA Cloud greenfield project, focus on the following aspects:
* A. Timeliness: Ensures that data is up-to-date and reflects the current state of the business. Outdated data can lead to incorrect decisions.
* C. Accuracy: Ensures that data is correct and free from errors. Inaccurate data can compromise business processes and reporting.
The other options are incorrect:
* B. Stability: While stability is important for system performance, it is not directly related to data quality.
* D. Efficiency: Efficiency pertains to process optimization and resource utilization, not data quality.
SAP S/4HANA Cloud References:
* Data Quality Management in SAP S/4HANA Cloud.
* Clean Core Principles.

To configure a dataflow to run regularly, SAP recommends two best-practice options:
* Option A: Correct. Using thedataflow schedulerin the SAP Customer Data Cloud Console is the most straightforward way to configure regular execution. You can define the schedule directly in the UI.
* Option B: Incorrect. Theidx.setDataflowendpoint is used to update dataflow configurations, not to schedule them.
* Option C: Correct. Usingextensionsand scheduling the dataflow via an extension endpoint provides flexibility and allows for advanced scheduling scenarios, such as triggering the dataflow based on external events.
* Option D: Incorrect. Theidx.createSchedulingendpoint is not a valid API endpoint for scheduling dataflows.
References:
* SAP Customer Data Cloud - Dataflow Scheduling
* Extensions and Custom Scheduling