Methodologies

The main methodologies to work with Big Data in their ecosystem are listed below:

An operation that consists in the comparison between experimental and control data sets. It is common in research and can be performed by means of machine learning and natural language processing.

An operation that aims at the extraction of useful information from data; it might employ methods like cloud computing (for database search) and visualization techniques (for displays of the data)

An operation that consists of training the machine to automatically perform tasks which involve automatic data management or classification. It can be efficiently handled by sensor-based computation such as multilinear subspace learning or Massively Parallel-Processing (MPP)

A set of tools that optimize search-based applications and infrastructures, like distributed file systems, distributed databases, cloud and High-Performance Computing infrastructure

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