For which of the following elements is an enterprise data warehouse best suited?

An enterprise data warehouse is designed to serve as a central repository of integrated data from various sources for the purposes of reporting and analysis. It effectively handles various types of data, including raw data, summary data, and metadata.

Raw data refers to unprocessed data collected directly from source systems, which can be stored in a data warehouse for future processing and analysis. Storing raw data allows organizations to maintain a complete historical record and perform thorough analyses as needed.

Summary data is also essential in a data warehouse as it provides aggregated information, which is useful for high-level reporting and decision-making. This data is often pre-processed to enhance performance and reduce the complexity of queries made by end-users.

Metadata, which includes information about data, such as definitions, data lineage, and formats, plays a crucial role in the management of a data warehouse. It helps users understand the data structure, facilitates data governance, and enhances data quality, making it easier to navigate through the data.

Given that an enterprise data warehouse can accommodate all these elements effectively, it is well-suited to house raw data, summary data, and metadata, which makes the most comprehensive choice the best answer.