Imagine you're working with a large data set in R and need to perform operations on a matrix that's not memory-efficient. How would you handle this situation?

When working with a large data set in R and facing memory limitations with a matrix, you can handle the situation by utilizing memory-mapping techniques to access data on disk instead of loading everything into memory at once. Another approach is to implement chunk-wise processing, where you operate on subsets of the matrix at a time to reduce memory usage. Additionally, if the matrix has a sparse structure, converting it to a sparse matrix representation can significantly reduce memory requirements while still allowing efficient operations. These strategies enable working with large matrices that do not fit entirely in memory.