What defines a set of practices for managing the data life cycle in an automated manner?

The correct choice focuses on the definition of "data operations," which encompasses a range of practices designed to manage the data life cycle through automation. Data operations ensure that processes related to data collection, processing, storage, and retrieval are streamlined and efficient, often utilizing automated workflows and tools. This approach allows organizations to handle data consistently and reliably, reducing the potential for human error and improving the overall management of data assets.

By implementing automated practices in the data life cycle, organizations can achieve better data governance, enhance data integrity, and ensure compliance with various regulations and standards. Data operations also involve monitoring and optimizing the performance of data systems, making it an essential aspect of managing data effectively in today’s digital landscape.

In contrast, data privacy focuses primarily on the protection of personal data and compliance with legal standards, data preparation involves the initial steps of cleansing and organizing data for analysis, and data science pertains to the analytical techniques used to extract insights from data. While important, these concepts do not specifically address the comprehensive management of the data life cycle through automation as data operations do.