big data research paper





Big data : the management revolution
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Spotlight onBig Datathe analytics that were used in the past. We can measure and therefore manage more precisely than ever before. We can make better predictions and smarter decisions. We can target more-effective interventions, and can do so in areas that so

The age ofbig data
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Mo Zhou was snapped up by IBM last summer, as a freshly minted Yale MBA, to join the technology companys fast-growing ranks ofdataconsultants. They help businesses make sense of an explosion ofdata Web traffic and social network comments, as well as

The digital universe in 2020:Big data bigger digital shadows, and biggest growth in the far east
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Welcome to the digital universea measure of all the digitaldatacreated, replicated, and consumed in a single year. Its also a projection of the size of that universe to the end of the decade. The digital universe is made up of images and videos on mobile phones uploaded

Are you ready for the era ofbig data
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But over the last few years, the volume ofdatahas exploded. In 15 of the US economys 17 sectors, companies with more than 1,000 employees store, on average, over 235 terabytes ofdata moredatathan is contained in the US Library of Congress. Reams ofdatastill flow

Big dataanalytics
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2011 by TDWI (TheDataWarehousing 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 info@tdwi.org. Product and company names mentioned herein may

Starfish: A Self-tuning System forBig DataAnalytics.
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ABSTRACT 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 stackwhich consists of an extensible MapReduce

Clouds,big data and smart assets: Ten tech-enabled business trends to watch
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Two of the original eight trends merged to form a megatrend around distributed cocreation. We also identified three

The promise and peril ofbig data
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According to a recent report1, the amount of digital content on the Internet is now close to five hundred billion gigabytes. This number is expected to double within a year. Ten years ago, a single gigabyte ofdataseemed like a vast amount of information. Now, we commonly

Thebig data revolution in healthcare
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An era of open information in healthcare is now under way. We have already experienced a decade of progress in digitizing medical records, as pharmaceutical companies and other organizations aggregate years of research and developmentdatain electronic databases.

Big datacomputing: creating revolutionary breakthroughs in commerce, science and society
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Advances in digital sensors, communications, computation, and storage have created huge collections ofdata capturing information of value to business, science, government, and society. For example, search engine companies such as Google, Yahoo!, and Microsoft

Thebig datarevolution in US health care: Accelerating value and innovation
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1 This estimate is based on a measure developed by McKinsey, estimated spending according to wealth,which is derived from a regression analysis of income and spending datafrom other countries in the Organisation of Economic Co-operation and Development. It

Clouds for scalablebig dataanalytics
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Advanceddatamining techniques and associated tools can help extract information from large, complex datasets that is useful in making informed decisions in many business and scientific applications including tax payment collection, market sales, social studies,

Big data : What it is and why you should care
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EXECUTIVE SUMMARYDatacreation is occurring at a record rate. In 2010, the world generated over 1ZB ofdata ; by 2014, we will generate 7ZB a year. Much of thisdata explosion is the result of a dramatic increase in devices located at the periphery of the

LinkedDataBig Data and the 4th Paradigm.
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Around 2006, the inception of LinkedDatahas led to a realignment of the Semantic Web vision and the realization thatdatais not merely a way to evaluate our theoretical considerations, but a key research enabler in its own right that inspires novel theoretical and

Big datainbigcompanies
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Big databurst upon the scene in the first decade of the 21st century, and the first organizations to embrace it were online and startup firms. Arguably, firms like Google, eBay, LinkedIn, and Facebook were built aroundbig datafrom the beginning. They didnt have to

Big datafor education:Datamining,dataanalytics, 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 collectdataon how long it takes him to master the material. After each assignment, a quiz will pop up on his screen

Puttingbig datato good use in neuroscience
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Big datahas transformed fields such as physics and genomics. Neuroscience is set to collect its ownbig datasets, but to exploit its full potential, there need to be ways to standardize, integrate and synthesize diverse types ofdatafrom different levels of analysis

Big Datafor Development
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Challenge# 1: Arrogance/naivety. Believing that the truth is in the ( big )data that the ( big enough)dataspeak for themselves, that all it takes is to beep digging and mining to unveil the truth, that more is always better etc. Apopheniaseeing patterns where none exists. If

The current state of business intelligence in academia: The arrival ofbig data .
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In December 2012, the AIS Special Interest Group on Decision Support, Knowledge and DataManagement Systems (SIGDSS) and the Teradata University Network (TUN) cosponsored the Business Intelligence Congress 3 and conducted surveys to assess

Distributed coordinate descent method for learning withbig data
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Abstract In this paper we develop and analyze Hydra: HYbriD cooRdinAte descent method for solving loss minimization problems withbig data . We initially partition the coordinates (features) and assign each partition to a different node of a cluster. At every iteration, each Smart grid is a technological innovation that improves efficiency, reliability, economics, and sustainability of electricity services. It plays a crucial role in modern energy infrastructure. The main challenges of smart grids, however, are how to manage different types of front-end

Why Big Data is abigdeal
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Alyssa Goodman,Big data computational biology, Gary King, information technology, Institute for Quantitative Social Science, Jeffrey Schnapp, Julio Frenk, medical privacy, quantitative methods, statistics, visualizations a zettabytedwarfs the prior record of human

Thebig dataopportunity
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Executive Summary The modern world generates a staggering quantity ofdataand the business of government is no exception. Across the public sector, extraordinary quantities of dataare amassed in the course of running public services from managing welfare Howbigisbig Science writer Stephen Strauss asks in his fun book for kids titled HowBig isBigand explains thatbigness is something no one can consume.In this book, we aim to answer this interesting question, but in the context of computerdata . In thebig dataera, we Big datarefers to large and complex massive amounts ofdatasets that it becomes difficult to process and analyze using traditionaldataprocessing technology. Over the past few years there has been an exponential growth in the rate of availabledatasets obtained from

Finito: A faster, permutable incremental gradient method forbig dataproblems
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Abstract Recent advances in optimization theory have shown that smooth strongly convex finite sums can be minimized faster than by treating them as a black boxbatchproblem. In this work we introduce a new method in this class with a theoretical convergence rate four

Howbig databecame sobig
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First, here are a few, well,datapoints:Big Datawas a featured topic this year at the World Economic Forum in Davos, Switzerland, with a report titled Big DataBigImpact.In March, the federal government announced $200 million in research programs forBig Data

Big dataresearch in information systems: Toward an inclusive research agenda.
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Abstract:Big datahas received considerable attention from the information systems (IS) discipline over the past few years, with several recent commentaries, editorials, and special issue introductions on the topic appearing in leading IS outlets. These papers present

Seizing the potential ofbig data
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2 and analyze consumer sentiment and generate recommendations across millions of customersa capability that was neutralizing the retailers sales force. Meanwhile, the competitor was becoming a platform where vendors could sell excess inventory by using

Recent advances and trends of cyber-physical systems andbig dataanalytics in industrial informatics
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AbstractIn todays competitive business environment, companies are facing challenges in dealing withbig dataissues for rapid decision making for improved productivity. Many manufacturing systems are not ready to managebig datadue to the lack of smart analytics

Big datafrom smalldata :datasharing in thelong tailof neuroscience
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The launch of the US BRAIN and European Human Brain Projects coincides with growing international efforts toward transparency and increased access to publicly funded research in the neurosciences. The need fordatasharing standards and neuroinformatics

Managingbig datafor scientific visualization
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Many areas of endeavor have problems withbig data . Some classical business applications have facedbig datafor some time (eg airline reservation systems), and newer business applications to exploitbig dataare under construction (egdatawarehouses, federations of

Big datasurveillance: Introduction
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Some definitions will help specify the character of the changes associated withbig data driven forms of surveillance. For our purposes, the notion of big data refers to both the unprecedented size of contemporary databases and the emerging techniques for making

Big datain healthcare hype and hope
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Digitized information is ubiquitous, a digital flood creating puddles and lakes, creeks and torrents, ofdata : numbers, words, music, images, video. Most recently, the rapid growth in the use of mobile devicessmart phones, laptops, tablets, personal sensorsis generating

Radoop: Analyzingbig datawith rapidminer and hadoop
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Abstract Working with largedatasets is increasingly common in research and industry. There are some distributeddataanalytics solutions like Hadoop, that offer high scalability and fault-tolerance, but they usually lack a user interface and only developers can exploit

We are all social scientists now: howbig data machine learning, and causal inference work together
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Information is being produced and stored at an unprec-edented rate. It might come from recording the publics daily life: people express their emotions on Facebook accounts, tweet opinions, call friends on cell phones, make statements on Weibo, post photographs on The recent pursuits emerging inbig dataprocessing, interpretation, collection, and organization have emerged in numerous sectors including business, industry, and not-for- profit organizations.Datasets such as customer transactions for a megaretailer, weather

Big dataprocessing in cloud environments
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In recent years, accompanied by lower prices of information and communications technology (ICT) equipment and networks, various items ofdatagleaned from the real world have come to be accumulated in clouddatacenters. There are increasing hopes that

Towards ultrahigh dimensional feature selection forbig data
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Abstract In this paper, we present a new adaptive feature scaling scheme for ultrahigh- dimensional feature selection onBig Data and then reformulate it as a convex semi-infinite programming (SIP) problem. To address the SIP, we propose an efficient feature generating

MegaODA large sample andBIG DATAtime trials: Maximum velocity analysis
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This third time trail of newly-released MegaODA™ software studies the fastest-to-analyze application, known as a 2x2 cross-classification table. Designs involving unweighted binary dataare arguably currently the most widely employed across quantitative scientific The business world is rapidly digitizing as companies embrace sensors, mobile devices, radio frequency identification, audio and video streams, software logs, and the Internet to predict needs, avert fraud and waste, understand relationships, and connect with

Big Data : Are you ready for blast-off
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A recently launched Japanese-US satellite will monitor global rainfall, helping meteorologists usebig dataanalytics to predict storms around the world As Technology of Business begins a month-long series of features on the theme ofBig Data we kick off with a QA backgrounder

Big dataforbigbusiness A taxonomy ofdatadriven business models used by start-up firms
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The purpose of this paper is to propose a taxonomy of business models used by start-up firms that rely ondataas a resource of major importance for their business aka datadriven business models (DDBMs). Furthermore, it proposes a DDBM framework to systematically

Topic modeling using topics from many domains, lifelong learning andbig data
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Abstract Topic modeling has been commonly used to discover topics from document collections. However, unsupervised models can generate many incoherent topics. To address this problem, several knowledge-based topic models have been proposed to

Big DataAnalysis: Challenges and Solutions
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AbstractWe live in on-demand, on-command Digital universe withdataprolifering by Institutions, Individuals and Machines at a very high rate. Thisdatais categories asBig Datadue to its sheer Volume, Variety, Velocity and Veracity. Most of thisdatais

Transparent and Flexible Network Management forBig DataProcessing in the Cloud.
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Abstract We introduce FlowComb, a network management framework that helpsBig Data processing applications, such as Hadoop, achieve high utilization and lowdataprocessing times. FlowComb predicts application network transfers, sometimes before they start, by

Architecting abig dataplatform for analytics
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For many years, companies have been buildingdatawarehouses 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 wheredatafrom

The emergence ofbig datatechnology and analytics
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Abstract The Internet has made new sources of vast amount ofdataavailable to business executives.Big datais comprised of datasets too large to be handled by traditional database systems. To remain competitive business executives need to adopt the new technologies

MegaODA large sample andBIG DATAtime trials: Separating the chaff
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Just-released MegaODAsoftware is capable of conducting UniODA analysis for an unlimited number of attributes using samples as large as one million observations. To minimize the computational burden associated with Monte Carlo simulation used to estimate

MegaODA large sample andBIG DATAtime trials: Harvesting the Wheat
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In research involving multiple tests of statistical hypotheses the efficiency of Monte Carlo (MC) simulation used to estimate the Type I error rate (p) is maximized using a two-step procedure. The first step is identifying the effects that are not statistically significant or ns.

Perspectives onbig dataandbig dataanalytics
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Nowadays companies are starting to realize the importance of using moredatain order to support decision for their strategies. It was said and proved through study cases thatMore datausually beats better algorithms . With this statement companies started to realize that

The networked readiness index 2014: Benchmarking ICT uptake in a world ofbig data
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When The Global Information Technology Report (GITR) and the Networked Readiness Index (NRI) were created more than 13 years ago, the attention of decision makers was focused on how to develop strategies that would allow them to benefit from what Time

Big dataand the ag sector: More than lots of numbers
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Abstract It seems that one cant go through a work day without seeing some mention ofBig Data its application and its potential to have unprecedented impact. The potential forBig Dataapplication in the agricultural sector is examined. The role of analytics and the variety IntroductionDataintensive computing is now starting to be considered as the basis for a new, fourth paradigm for science. Two factors are encouraging this trend. First, vast amounts ofdataare becoming available in more and more application areas. Second, the

Organizational alignment is key tobig datasuccess
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One was the promise of improveddatadriven decision making. Everybody agreed on that in principle. All organizations expressed an interest in being able to do that, though what that means for different organizations varies. Some organizations are focused on strengthening

In head-hunting,big datamay not be such abigdeal
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A. I think theres been a fairly recent confluence of the ability to crunch lots ofdataat fairly low cost, venture capital investments that support new businesses in this field, and changes in what people expect. Leadership is a perennially difficult, immeasurable problem, so

Big datausing cloud computing
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AbstractBig Datais adataanalysis methodology enabled by recent advances in technologies and architecture. However,big dataentails a huge commitment of hardware and processing resources, making adoption costs ofbig datatechnology prohibitive to small

Managingbig data
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CO-SPONSORED BY tdwi. org 12013 by TDWI (TheDataWarehousing 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 info@ tdwi. org.

Broom: Sweeping out garbage collection frombig datasystems
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Abstract Many popular systems for processing big data are implemented in high-level programming languages with automatic memory management via garbage collection (GC). However, high object churn and large heap sizes put severe strain on the garbage collector.

Securingbig datahadoop: a review of security issues, threats and solution
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AbstractHadoop projects treat Security as a top agenda item which in turn represents which is again classified as a critical item. Be it financial applications that are deemed sensitive, to healthcare initiatives, Hadoop is traversing new territories which demand