The main advantages of distributed data computing include the lower cost of processing data, having multiple control centers that reduce the risk of a system breakdown, and improved efficiency. Another advantage is that distributed data computing can utilize computers in separate locations as long as they're connected via a network..
Companies can typically save a money by switching to multiple minicomputers instead of using a small number of mainframe machines that serve as centralized servers. Having multiple computers processing the same data means that a malfunction in one of the computers doesn’t jeopardize the entire computing process across the network. Companies that use distributed data computing can break data and statistical problems into separate modules and have each node process them in parallel, cutting down the time necessary to complete the computations.