Our world is covered with digital data from social networks, blogs, business, science, and engineering. Data-intensive computing facilitates the understanding of the complex problems that have got to process massive amounts of data. Through the latest classes of software, algorithms, and hardware, data-intensive applications can provide timely and meaningful analytical leads to exponentially growing data complexity and associated analysis requirements. This emerging area brings out a large number of challenges that are different from traditional high-performance computing.
This reference for computing professionals and researchers describes the size of the field, the key challenges, the state of the art, and therefore the characteristics of likely approaches that future data-intensive problems would require. Chapters cover general principles and methods for designing such systems and managing and analyzing many data sets of today that sleep in the cloud, and describe example applications in cyber-security and bioinformatics, and illustrate these principles in practice.
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