What should you implement to ensure data transformation steps happen only if previous steps succeed?

Implementing conditional execution is fundamental to ensuring that data transformation steps only occur if the preceding steps have been successfully completed. This approach allows systems to evaluate the success or failure of prior operations before proceeding to the next set of actions. If the conditions set for the previous steps are not met, the transformation process can be halted or rerouted accordingly, preventing potential errors and inconsistencies in data processing.

This method is particularly essential in data workflows where the integrity and accuracy of the data are paramount. By utilizing conditional execution, you can establish a dependency chain among various transformation steps, thus promoting reliability in processing, as subsequent operations are contingent upon the successful outcome of their predecessors.

The other options are not suitable for this specific requirement. Sequential execution may imply that tasks are processed one after the other, but it does not inherently ensure that a subsequent task will only run if the prior one succeeds. Parallel execution allows multiple transformations to occur simultaneously and does not account for success or failure relationships. Trigger-based execution depends on pre-defined triggers to initiate processes, which might not be directly related to the success of previous steps, making it less effective for this particular need.