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In Dask, when reading a Parquet dataset, the division information is stored in the metadata of the Parquet file in the form of row groups. Each row group represents a logical division of the dataset and contains metadata about its start and end locations within the file. Dask uses this division information to efficiently distribute the data across multiple processing units. When performing operations on the dataset, Dask splits the data based on the division information and executes the operations on each partition independently. The final results are then combined to form the final output. This approach allows Dask to efficiently process large Parquet datasets in a parallel and distributed manner.