Springer, 2014. — 100 p. — ISBN: 3319062441, 9783319062457This Springer Brief provides a comprehensive overview of the background and recent developments of big data. The value chain of big data is divided into four phases: data generation, data acquisition, data storage and data analysis. For each phase, the book introduces the general background, discusses technical challenges and reviews the latest advances. Technologies under discussion include cloud computing, Internet of Things, data centers, Hadoop and more. The authors also explore several representative applications of big data such as enterprise management, online social networks, healthcare and medical applications, collective intelligence and smart grids. This book concludes with a thoughtful discussion of possible research directions and development trends in the field. Big Data: Related Technologies, Challenges and Future Prospects is a concise yet thorough examination of this exciting area. It is designed for researchers and professionals interested in big data or related research. Advanced-level students in computer science and electrical engineering will also find this book useful.Contents: Introduction.- Related Technologies.- Big Data Generation and Acquisition.- Big Data Storage.- Big Data Analysis.- Big Data Applications.- Open Issues and Outlook.
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Morgan Kaufmann , 2013. – 370 p. – ISBN: 0124058914, 9780124058910
The Morgan Kaufmann Series on Business Intelligence
Data Warehousing in the Age of the Big Data will help you and your organization make the most of unstructured data with your existing Data Warehouse. As Big Data continues to revolutionize how we use data, it doesn't have to create more confusion.
Morgan Kaufmann, 2013. — 130 p. — ISBN: 0124173195, 9780124173194
Big Data Analytics will assist managers in providing an overview of the drivers for introducing big data technology into the organization and for understanding the types of business problems best suited to big data analytics solutions, understanding the value drivers and benefits, strategic planning, developing a...
CRC Press, 2011. — 542 p. — 2nd ed. — ISBN: 1439860912, 9781439860915
The second edition of a bestseller, Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data is still the only book, to date, to distinguish between statistical data mining and machine-learning data mining. The first edition, titled Statistical Modeling...