What systems are designed for moving, cleaning, and processing data?

The correct answer is the data pipeline. Data pipelines are systems specifically designed to automate and streamline the process of moving, cleaning, and processing data from one system to another, usually in a way that allows for real-time data processing and analysis.

The primary function of a data pipeline includes extracting data from various sources, transforming that data as needed to ensure it is in a suitable format, and then loading it into a destination, such as a data warehouse or a database. This process is often referred to as Extract, Transform, Load (ETL). Data pipelines typically handle large volumes of data and can integrate data from multiple sources, ensuring that the data is reliable and accessible for further analysis.

In contrast, the other options serve different purposes within the realm of data management. Data analytics involves analyzing and interpreting data to derive actionable insights; while useful, it does not focus on the movement or cleaning process. A data mart is a repository of data specifically designed for a particular line of business, and it is more about data storage and retrieval rather than the handling process itself. Data sync refers to the process of ensuring that two or more datasets are consistent and up-to-date across different platforms, but it does not encompass the full functionality of data movement and processing like