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In the context of a Professional Machine Learning Engineer's role, particularly when defining how the model output should be utilized to address a business problem, which of the following objectives is most critical to ensure the model's success in a real-world scenario? Consider the need for alignment with business objectives, the importance of model interpretability, and the potential impact on decision-making processes. Choose the best option.
A
Developing the most complex machine learning model possible to ensure high accuracy
B
Focusing solely on improving the model's accuracy without considering the business context
C
Ensuring that the model's outputs are directly aligned with the business objectives and can be interpreted by stakeholders to inform decision-making
D
Prioritizing data extraction and transformation tasks over model applicability to business needs
E
Both ensuring alignment with business objectives and improving model interpretability are equally important