What is data partitioning in distributed systems?

Data partitioning is the process of splitting datasets across multiple nodes to enable parallel processing.

Partitioning distributes data horizontally based on keys, ranges, or hashing strategies. It improves scalability, fault tolerance, and query performance. However, poor partitioning leads to data skew, where some nodes handle disproportionate load.