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Extremely large, diverse, and complex data sets are generated from scientific instruments, sensors, social media, Internet and other applications End to end management, analysis, and visualization of these large, distributed and heterogeneous data sets has been a major challenge impeding scientific discovery and technological advancement The 2013 IEEE international Conference on Big Data will provide the scientific community a dedicated forum for discussing state of the art research, development, and deployment efforts for the end to end management, storage, sharing, analysis, and visualization of very large data sets The BigData2012 workshop will be an excellent forum to help the community define the current state, determine future goals, and present architectures and services for future data management technologies supporting Big Data and data intensive computing.

Big data

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Cloud is a common metaphor for an Internet accessible infrastructure (e g data storage and computing hardware) which is hidden from users Cloud Computing makes data truly mobile and a user can simply access a chosen cloud with any internet accessible device In Cloud Computing, IT related capabilities are provided as services, accessible without requiring detailed knowledge of the underlying technology 1 Cloud Architecture 2 MapReduce Optimization and Applications 3 Cloud Security, Privacy and Accountability 4 Cloud Services and Applications 5 Virtualization 6 HPC on Cloud 7 IoT and Mobile Cloud 8 Big Data.

Big data. --- Cloud computing.

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"Principles of Big Data helps readers avoid the common mistakes that endanger all Big Data projects. By stressing simple, fundamental concepts, this book teaches readers how to organize large volumes of complex data, and how to achieve data permanence when the content of the data is constantly changing. General methods for data verification and validation, as specifically applied to Big Data resources, are stressed throughout the book. The book demonstrates how adept analysts can find relationships among data objects held in disparate Big Data resources, when the data objects are endowed with semantic support (i.e., organized in classes of uniquely identified data objects). Readers will learn how their data can be integrated with data from other resources, and how the data extracted from Big Data resources can be used for purposes beyond those imagined by the data creators. . Learn general methods for specifying Big Data in a way that is understandable to humans and to computers. . Avoid the pitfalls in Big Data design and analysis. . Understand how to create and use Big Data safely and responsibly with a set of laws, regulations and ethical standards that apply to the acquisition, distribution and integration of Big Data resources"--Provided by publisher.

Information systems --- big data --- datawarehousing

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Big data --- Data mining --- Economics

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"In conclusion as you come to the end of this book, the concept of a Data Warehouse and its primary goal of serving the enterprise version of truth, and being the single platform for all the source of information will continue to remain intact and valid for many years to come. As we have discussed across many chapters and in many case studies, the limitations that existed with the infrastructures to create, manage and deploy Data Warehouses have been largely eliminated with the availability of Big Data technologies and infrastructure platforms, making the goal of the single version of truth a feasible reality. Integrating and extending Big Data into the Data Warehouse, and creating a larger decision support platform will benefit businesses for years to come. This book has touched upon governance and information lifecycle management aspects of Big Data in the larger program, however you can reuse all the current program management techniques that you follow for the Data Warehouse for this program and even implement agile approaches to integrating and managing data in the Data Warehouse. Technologies will continue to evolve in this spectrum and there will be more additions of solutions, which can be integrated if you follow the modular integration approaches to building and managing the Data Warehouse. The Appendix sections contain many more case studies and a special section on Healthcare Information Factory based on Big Data approaches. These are more guiding posts to help you align your thoughts and goals to building and integrating Big Data in your Data Warehouse"--

Information systems --- big data --- data warehousing --- datawarehousing