Data gravity describes how large datasets influence where compute and storage should be placed because their location affects latency and cost.

Data gravity describes how large datasets influence where compute and storage should be placed because their location affects latency and cost.

• A. Data gravity means large datasets attract services and workloads; the location of data influences where compute and storage are placed, affecting latency and cost.
• B. Data gravity is a theory about gravity in data centers only.
• C. Data gravity refers to data encryption strength.
• D. Data gravity requires data to be moved constantly.

Answer: (A)

Data gravity is about data attracting the compute and storage resources that need to work with it. When you have large datasets, moving that data around to wherever you want to run processing becomes costly and slow. So it’s more efficient to place compute and storage near the data, or even co-locate them in the same region or system. This reduces data transfer time, lowers network costs, and improves overall latency, making analytics, processing, and data-driven workloads faster and cheaper. The other ideas don’t fit this concept. It’s not a theory about gravity in data centers, nor a measure of encryption strength, and it doesn’t require data to be moved constantly.

Data gravity is about data attracting the compute and storage resources that need to work with it. When you have large datasets, moving that data around to wherever you want to run processing becomes costly and slow. So it’s more efficient to place compute and storage near the data, or even co-locate them in the same region or system. This reduces data transfer time, lowers network costs, and improves overall latency, making analytics, processing, and data-driven workloads faster and cheaper.

The other ideas don’t fit this concept. It’s not a theory about gravity in data centers, nor a measure of encryption strength, and it doesn’t require data to be moved constantly.