Google Professional Machine Learning Engineer
Get started today
Ultimate access to all questions.
Ultimate access to all questions.
In the context of preparing and processing data for machine learning models, data governance is crucial for ensuring the integrity and reliability of the models. Considering a scenario where a company is deploying ML models to predict customer behavior, which of the following best describes the role of data governance in this process? (Choose one correct option)
Explanation:
Data governance is essential in the ML data preparation and processing pipeline as it establishes a framework for managing data responsibly. This includes ensuring data quality, protecting data privacy and security, facilitating regulatory compliance, and enabling effective decision-making. The correct option highlights the comprehensive role of data governance in setting policies and standards for data usage, which is critical for the integrity of ML models. Incorrect options either misrepresent the purpose of data governance or underestimate its importance in the ML lifecycle.