This important and timely text/reference presents a detailed review of
high-performance computing infrastructures for next-generation big data
and fast data analytics.
Comprehensively covering a diverse range of computer systems and proven
techniques for high-performance big-data analytics, the book also
presents case studies, practical guidelines, and best practices for
enabling decision-making toward implementing the appropriate computer
systems and approaches.
Topics and features: includes case studies and learning activities
throughout the book, and self-study exercises at the end of every
chapter; presents detailed case studies on social media analytics for
intelligent businesses, and on big data analytics in the healthcare
sector; describes the network infrastructure requirements for effective
transfer of big data, and the storage infrastructure requirements of
applications which generate big data; examines real-time analytics
solutions, such as machine data analytics and operational analytics;
introduces in-database processing and in-memory analytics techniques for
data mining; discusses the use of mainframes for handling real-time big
data, and the latest types of data management systems for big and fast
data analytics; provides information on the use of cluster, grid and
cloud computing systems for big data analytics and data-intensive
processing; reviews the peer-to-peer techniques and tools, and the
common information visualization techniques, used in big data analytics.
Software engineers, cloud professionals and big data scientists will
find this book to be an informative and inspiring read, highlighting the
indispensable role data analytics will play in shaping a smart future.
