An SAP Datasphere Data Flow is a powerful tool for data integration and transformation. Its core capabilities include:

1. Integrating data from multiple sources: A data flow can combine datasets from various source systems (e.g., SAP S/4HANA, cloud storage, other databases) into a single target table.

2. Parallel processing: A single data flow can be designed with multiple, independent branches to load data into several different target tables simultaneously, which improves performance.

3. Advanced transformations: For complex logic that cannot be handled by standard operators, the Script operator allows users to embed and execute Python code to transform the data.

A. Write data to a table in a different SAP Datasphere tenant. A Data Flow operates within the context of a single SAP Datasphere tenant. Writing to another tenant is not a direct, standard capability of the Data Flow object itself.

C. Delete records from a target table. Data Flows support Append, Upsert, and Truncate load types. They do not provide a standard operator for selectively deleting specific records from a target table based on source data conditions.

1. SAP Help Portal - What Is a Data Flow?: This official documentation states

"You use a data flow to integrate

transform

and combine data from one or more source objects and load it into one or more target objects." This supports options B and D.

2. SAP Help Portal - Data Flow Execution: This page confirms parallel processing: "If your data flow has multiple branches that are independent of each other

they are processed in parallel." This directly supports option D.

3. SAP Help Portal - Script Operator: This document details the Python script functionality: "You can use the Script operator to write a Python script to transform your data." This supports option E.

4. SAP Help Portal - Loading Data into a Target Table: This page describes the available load types (Append

Truncate

Upsert)

confirming the absence of a selective Delete operation

which makes option C incorrect.