RDD, or Resilient Distributed Dataset, is a powerful data structure used in big data processing that allows for efficient and fault-tolerant data manipulation. It is a collection of data elements that can be divided into smaller chunks and distributed across multiple nodes in a cluster, making it highly scalable and resilient to failures. RDDs are immutable, meaning they cannot be modified once created, but can be transformed through various operations such as map, filter, and reduce. This allows for parallel processing of large datasets, making RDDs a crucial component in the world of big data analytics. With its ability to handle massive amounts of data and withstand failures, RDDs have become an essential tool for data scientists and engineers in tackling complex data challenges.