Scalability: As visualization techniques are used more and more in data mining tools, it becomes important to address scalability issue. Fundamentally, the reason for scalable solutions is to be able to build a good data mining model as quickly as possible. This offers two benefits, a) there is value in being able to deploy and use the model sooner rather than later and b) faster turnaround times yield better models. Time previously spent waiting for results can instead be devoted to finding the model that result in the best and most reliable solution. Making data mining tools scalable requires hardware scalability and parallel algorithms. The goal of hardware scalability is to provide high performance by adding modestly priced processor building blocks (or nodes) in such a way that performance scales linearly.

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