Cold data is accessed infrequently while hot data is accessed frequently and needs rapid availability is correct.

Hot data describes datasets that are accessed frequently and that require low latency and quick retrieval. Systems or storage classes for hot data are optimized for immediate availability and performance so applications can read and write rapidly.

Cold data is characterized by infrequent access and by tolerance for slower retrieval times which makes it suitable for lower cost storage tiers or archives. The primary differentiator is the access pattern and the required availability rather than format or location.

Hot data tends to be more expensive to retain while cold data normally costs less to store is incorrect because cost differences are a consequence of performance and access requirements rather than the defining attribute. Cost may often align with hot versus cold but it is not the core distinction.

Hot data is structured while cold data is unstructured is incorrect because whether data is structured or unstructured does not determine its temperature. Both structured and unstructured datasets can be hot or cold depending on how often they are accessed.

Hot data is stored in primary cloud storage while cold data is kept on local on premise servers is incorrect because cold data is commonly placed into lower cost cloud storage tiers or archival services rather than necessarily being kept on premise. The classification is about access frequency and availability rather than physical location.

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