big data analytics


Big data analytics
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2011 by TDWI (The Data Warehousing InstituteTM), a division of 1105 Media, Inc. All rights reserved. Reproductions in whole or in part are prohibited except by written permission. E-mail requests or feedback to Product and company names mentioned herein may

Big data , analytics and the path from insights to value
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To help organizations understand the opportunity of information and advanced analytics , MIT Sloan Management Review partnered with the IBM Institute for Business Value to conduct a survey of nearly 000 executives, managers and analysts working across more

Starfish: A Self-tuning System for Big Data Analytics .
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Timely and cost-effective analytics over Big Data is now a key ingredient for success in many businesses, scientific and engineering disciplines, and government endeavors. The Hadoop software stack which consists of an extensible MapReduce execution engineMuch big data already resides in the cloud, and this trend will increase in the future. For example, IT research and advisory firm Gartner estimates that, by 201 more than half of large companies data will be stored in the cloud ( This trend requires that

Big data for education: Data mining, data analytics , and web dashboards
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In the future, her younger brother Richard is likely to learn reading through a computerized software program. As he goes through each story, the computer will collect data on how long it takes him to master the material. After each assignment, a quiz will pop up on his screen

Recent advances and trends of cyber-physical systems and big data analytics in industrial informatics
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In todays competitive business environment, companies are facing challenges in dealing with big data issues for rapid decision making for improved productivity. Many manufacturing systems are not ready to manage big data due to the lack of smart analytics tools. Germany

Big data analytics in the cloud: Spark on hadoop vs mpi/openmp on beowulf.
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One of the biggest challenges of the current big data landscape is our inability to process vast amounts of information in a reasonable time. In this work, we explore and compare two distributed computing frameworks implemented on commodity cluster architectures

Perspectives on big data and big data analytics
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Nowadays companies are starting to realize the importance of using more data in order to support decision for their strategies. It was said and proved through study cases that More data usually beats better algorithms . With this statement companies started to realize that

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ABSTRACT Today Big Data draws a lot of attention in the IT world. The rapid rise of the Internet and the digital economy has fuelled an exponential growth in demand for data storage and analytics, and IT department are facing tremendous challenge in protecting and

How AUDI AG Established Big Data Analytics in Its Digital Transformation.
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Digital transformation, which often includes establishing big data analytics capabilities, poses considerable challenges for traditional manufacturing organizations, such as car companies. Successfully introducing big data analytics requires substantial organizational

A survey on big data analytics : challenges, open research issues and tools
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A huge repository of terabytes of data is generated each day from modern information systems and digital technologies such as Internet of Things and cloud computing. Analysis of these massive data requires a lot of efforts at multiple levels to extract knowledge for

Architecting a big data platform for analytics
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For many years, companies have been building data warehouses to analyse business activity and produce insights for decision makers to act on to improve business performance. These traditional analytical systems are often based on a classic pattern where data from

Big data analytics in supply chain management: Trends and related research
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ABSTRACT Big Data Analytics offers vast prospects in todays business transformation. Whilst big data have remarkably captured the attentions of both practitioners and researchers especially in the financial services and marketing sectors, there is a myriad of Internet of Things and big data are two sides of the same coin. The advancement of Information Technology (IT) has increased daily leading to connecting the physical objects/devices to the Internet with the ability to identify themselves to other devices. This

A study on privacy preserving techniques in big data analytics
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The growing need for computing on bigdata is getting higher, the three basic dimensions of big data are (referred as 3V challenges) high volume, variety and velocity. The other upcoming challenge in the area of bigdata is Veracity, which means the trustworthiness of

Leveraging big data analytics and Hadoop in developing Indias healthcare services
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In this paper, we analyze and reveal the benefits of Big Data Analytics and Hadoop in the applications of Healthcare where the data flow to and from is in massive volume. The developing countries like India with huge population faces various problems in the field ofUBILYTICS We refer to the use of mul- tiple networked devices in our local environment to enable deep and dynamic analysis of massive, hetero geneous, and multiscale data anytime, anywhere as ubiquitous analytics , or ubilytics. This approach not only liberates analysts from the confines This book is a concise and easy-to-understand tutorial for big data and Spark. It will help you learn how to use Spark for a variety of big data analytic tasks. It covers everything that you need to know to productively use Spark. One of the benefits of purchasing this book is that it

A framework for secure healthcare systems based on big data analytics in mobile cloud computing environments
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In this paper we introduce a framework for Healthcare Information Systems (HISs) based on big data analytics in mobile cloud computing environments. This framework provides a high level of integration, interoperability, availability and sharing of healthcare data among

Knowledge bases in the age of big data analytics
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This tutorial gives an overview on state-of-the-art methods for the automatic construction of large knowledge bases and harnessing them for data and text analytics . It covers both big data methods for building knowledge bases and knowledge bases being assets for big data