Simulation and big data
Big unstructured data is often analyzed nowadays, or used as auxiliary information. Running simulations on big data is a challenge.
Big data can be too large to fit in the memory of a desktop computer. Whenever this happens, basically three options are available to choose from. The first option is to just use a more powerful server with a larger amount of memory for your computations. Second, the data can also be stored efficiently in a database and we connect to the database for analysis. Typically, only a subset of the data is of interest, so we can just grab the interesting parts of the database, import it to R, do the analysis, and export the results back to the database. Since R has excellent features and APIs for connecting ...
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