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Big Data computing and clouds: Trends and future directions

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This paper discusses approaches and environments for carrying out analytics on Clouds for Big Data applications. It revolves around four important areas of analytics and Big Data, namely (i) data management and supporting architectures; (ii) model development and scoring; (iii) visualisation and user interaction; and (iv) business models. Through a detailed survey, we identify possible gaps in technology and provide recommendations for the research community on future directions on Cloud-supported Big Data computing and analytics solutions

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ABSTRACT

This paper discusses approaches and environments for carrying out analytics on Clouds for Big Data applications.
It revolves around four important areas of analytics and Big Data, namely (i) data management and supporting architectures; (ii) model development and scoring; (iii) visualisation and user interaction; and (iv) business models. Through a detailed survey, we identify possible gaps in technology and provide recommendations for the research community on future directions on Cloud-supported Big Data computing and analytics solutions

INTRODUCTION
Society is becoming increasingly more instrumented and as a result, organisations are producing and storing vast amounts of data. Managing and gaining insights from the produced data is a challenge and key to competitive advantage. Analytics solutions that mine structured and unstructured data are important as they can help organisations gain insights not only from their privately acquired data, but also from large amounts of data publicly available on the Web [118]. The ability to cross-relate private information on consumer preferences and products with information from tweets, blogs, product evaluations, and data from social networks opens a wide range of possibilities for organisations to understand the needs of their customers, predict their wants and demands, and optimise the use of resources. This paradigm is being popularly termed as Big Data

Despite the popularity on analytics and Big Data, putting them into practice is still a complex and time consuming endeavour. As Yu [136] points out, Big Data offers substantial value to organisations willing to adopt it, but at the same time poses a considerable number of challenges for the realisation of such added value. An organisation willing to use analytics technology frequently acquires expensive software licences; employs large computing infrastructure; and pays for consulting hours of analysts who work with the organisation to better understand its business, organise its data, and integrate it for analytics [120]

Year : 2014

Publisher : ELSEVIER

By : Marcos D. Assunção , Rodrigo N. Calheiros , Silvia Bianchi , Marco A.S. Netto ,Rajkumar Buyyab

File Information : English Language / 13 Page / Size :711 K

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سال : 2014

ناشر : ELSEVIER

کاری از : Marcos D. Assunção , Rodrigo N. Calheiros , Silvia Bianchi , Marco A.S. Netto ,Rajkumar Buyyab

اطلاعات فایل : زبان انگلسی / 13 صفحه / حجم :711 K

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