Which object stores large volumes of raw data in a data lake?

• A. Data Lakes
• B. Data Models
• C. Activation Targets
• D. Segments

Answer: (A)

Data lakes are built to store large volumes of raw data in its native form. A data lake serves as a centralized repository that holds data in its unprocessed state—whether logs, JSON, images, videos, sensor streams, or other formats—without requiring upfront schema or extensive transformation. This design lets you keep data in its original, most detailed form and decide later how to analyze or model it, which is essential for big data and advanced analytics workloads.

The other terms don’t describe a storage location for raw data at scale. Data models define schemas and structures for data, but they don’t themselves store raw data. Activation targets isn’t a standard concept for storing raw data. Segments refer to partitions or subsets of data for processing or query performance, not the primary storage of raw data.