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Applied Big Data Analytics(Revised): Business Inteigence,Health Informatics,Capital Market,Analytics for Life Sciences

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Applied Big Data Analytics(Revised): Business Inteigence,Health Informatics,Capital Market,Analytics for Life Sciences

Applied Big Data Analytics(Revised): Business Inteigence,Health Informatics,Capital Market,Analytics for Life Sciences by ajit roy
English | July 1, 2015 | ISBN: N/A | ASIN: B010SSKSP0 | 753 pages | AZW3 | 7.84 Mb

Data pours into millions of computers every moment of every day. It is estimated that the total accumulated data stored on computers worldwide is about 300 exabytes.The annual transmission of data is estimated at about 1.9 zettabytes i.e.1900 billion gigabytes. Due to the tremendous amount of data generated daily from fields such as business, research, and sciences, big data is everywhere and represents huge opportunities to those who can use it effectively. In the past, this information was simply ignored and opportunities were missed. Realizing the great importance of big data, organizations scramble to find hidden information buried in big data and try to make the best use of it. Presently “big data” is a hot topic and getting a lot of media and business attention. Therefore, alternative management and processing methods have to be created to handle this complex and unstructured data size. Over recent times, the concepts of “big data” and “big data analytics” have become ubiquitous. It is hard to visit a web site, open a newspaper, or read a magazine that does not refer to one or both of those phrases. Yet the technologies that are incorporated into big data are massive parallelism, huge data volumes, data distribution, high-speed networks, high-performance computing, task and thread management, and data mining and analytics. Big Data is the result of practically everything in the world being monitored and measured, creating data faster than the available technologies can store, process or manage it. Presently there has been a surge of unstructured data, making up as much as 80% of new data that requires attention for management. Big Data results in three basic challenges: storing, processing and managing it efficiently. Scale-out architectures have been developed to store large amount of data and purpose-built appliances have improved the processing capability. The next frontier is learning how to manage Big Data throughout its entire lifecycle. To tackle the challenges of Big Data, novel approaches and tools have emerged. The technology required for big-data computing is developing at a satisfactory rate due to market forces and technological evolution. This book entitled 'Applied Big Data Analytics' presents a mix of theory and real world cases that discuss the technical and practical issues related to Big Data in intelligent information management. This book provides rich topics of big data management, technologies, and applications.
The edited book on 'Applied Big Data Analytics' reveals how to fully apply the tools and techniques in various fields. The book will certainly be invaluable to wide audiences of professionals, decision-makers, and consultants involved in analytics particularly the new comers in the areas. It will also be exceptionally useful to students of analytics in any graduate, undergraduate, or certificate program. The project could not have been successful without the whole hearted support of the valued contributors of the book. Simply I am grateful to all of them.