The world is awash with digital data from social networks, blogs,
business, science, and engineering. Data-intensive computing facilitates
understanding of complex problems that must process massive amounts of
data. Through the development of new classes of software, algorithms,
and hardware, data-intensive applications can provide timely and
meaningful analytical results in response to exponentially growing data
complexity and associated analysis requirements. This emerging area
brings many challenges that are different from traditional
high-performance computing. This reference for computing professionals
and researchers describes the dimensions of the field, the key
challenges, the state of the art, and the characteristics of likely
approaches that future data-intensive problems will require. Chapters
cover general principles and methods for designing such systems and for
managing and analyzing the big data sets of today that live in the
cloud, and describe example applications in bioinformatics and
cybersecurity that illustrate these principles in practice.
