Efficient stream analysis and its application to big data processing
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In 1968, 140 IT companies where solicited to build the ARPANET network. Most of them regarded the project as outlandish and only 12 bid, while today there are 3:4 billions Internet users. The advent of Internet in the 90s, the commercial outbreak of cloud computing in the 2000s and the growing use of connected mobile devices since 2009 pushed the telecommunication and IT world into a new stage of interconnectivity. Researchers and practitioners understood that the massive amount of available data entailed new opportunities as well as challenges. In particular, common data management techniques...
In 1968, 140 IT companies where solicited to build the ARPANET network. Most of them regarded the project as outlandish and only 12 bid, while today there are 3:4 billions Internet users. The advent of Internet in the 90s, the commercial outbreak of cloud computing in the 2000s and the growing use of connected mobile devices since 2009 pushed the telecommunication and IT world into a new stage of interconnectivity. Researchers and practitioners understood that the massive amount of available data entailed new opportunities as well as challenges. In particular, common data management techniques where not tailored to match this features and, soon enough, the term Big Data emerged to capture all of these characteristics. The aim of this book is to design novel algorithms in the data streaming model, or extend current solutions, to solve practical issues in Big Data applications.
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