Scaling Complex Analytical Processing On Graph Structured Data Using Map Reduce

Download Scaling Complex Analytical Processing On Graph Structured Data Using Map Reduce full books in PDF, epub, and Kindle. Read online Scaling Complex Analytical Processing On Graph Structured Data Using Map Reduce ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!

Data-Intensive Text Processing with MapReduce

Author : Jimmy Lin
Publisher : Springer Nature
ISBN 13 : 3031021363
Total Pages : 171 pages
Book Rating : 4.0/5 (31 download)

DOWNLOAD NOW!

Book Synopsis Data-Intensive Text Processing with MapReduce by : Jimmy Lin

Download or read book Data-Intensive Text Processing with MapReduce written by Jimmy Lin and published by Springer Nature. This book was released on 2022-05-31 with total page 171 pages. Available in PDF, EPUB and Kindle. Book excerpt: Our world is being revolutionized by data-driven methods: access to large amounts of data has generated new insights and opened exciting new opportunities in commerce, science, and computing applications. Processing the enormous quantities of data necessary for these advances requires large clusters, making distributed computing paradigms more crucial than ever. MapReduce is a programming model for expressing distributed computations on massive datasets and an execution framework for large-scale data processing on clusters of commodity servers. The programming model provides an easy-to-understand abstraction for designing scalable algorithms, while the execution framework transparently handles many system-level details, ranging from scheduling to synchronization to fault tolerance. This book focuses on MapReduce algorithm design, with an emphasis on text processing algorithms common in natural language processing, information retrieval, and machine learning. We introduce the notion of MapReduce design patterns, which represent general reusable solutions to commonly occurring problems across a variety of problem domains. This book not only intends to help the reader "think in MapReduce", but also discusses limitations of the programming model as well. Table of Contents: Introduction / MapReduce Basics / MapReduce Algorithm Design / Inverted Indexing for Text Retrieval / Graph Algorithms / EM Algorithms for Text Processing / Closing Remarks

Frontiers in Massive Data Analysis

Author : National Research Council
Publisher : National Academies Press
ISBN 13 : 0309287812
Total Pages : 191 pages
Book Rating : 4.3/5 (92 download)

DOWNLOAD NOW!

Book Synopsis Frontiers in Massive Data Analysis by : National Research Council

Download or read book Frontiers in Massive Data Analysis written by National Research Council and published by National Academies Press. This book was released on 2013-09-03 with total page 191 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data mining of massive data sets is transforming the way we think about crisis response, marketing, entertainment, cybersecurity and national intelligence. Collections of documents, images, videos, and networks are being thought of not merely as bit strings to be stored, indexed, and retrieved, but as potential sources of discovery and knowledge, requiring sophisticated analysis techniques that go far beyond classical indexing and keyword counting, aiming to find relational and semantic interpretations of the phenomena underlying the data. Frontiers in Massive Data Analysis examines the frontier of analyzing massive amounts of data, whether in a static database or streaming through a system. Data at that scale-terabytes and petabytes-is increasingly common in science (e.g., particle physics, remote sensing, genomics), Internet commerce, business analytics, national security, communications, and elsewhere. The tools that work to infer knowledge from data at smaller scales do not necessarily work, or work well, at such massive scale. New tools, skills, and approaches are necessary, and this report identifies many of them, plus promising research directions to explore. Frontiers in Massive Data Analysis discusses pitfalls in trying to infer knowledge from massive data, and it characterizes seven major classes of computation that are common in the analysis of massive data. Overall, this report illustrates the cross-disciplinary knowledge-from computer science, statistics, machine learning, and application disciplines-that must be brought to bear to make useful inferences from massive data.

Big Data of Complex Networks

Author : Matthias Dehmer
Publisher : CRC Press
ISBN 13 : 1315353598
Total Pages : 290 pages
Book Rating : 4.3/5 (153 download)

DOWNLOAD NOW!

Book Synopsis Big Data of Complex Networks by : Matthias Dehmer

Download or read book Big Data of Complex Networks written by Matthias Dehmer and published by CRC Press. This book was released on 2016-08-19 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data of Complex Networks presents and explains the methods from the study of big data that can be used in analysing massive structural data sets, including both very large networks and sets of graphs. As well as applying statistical analysis techniques like sampling and bootstrapping in an interdisciplinary manner to produce novel techniques for analyzing massive amounts of data, this book also explores the possibilities offered by the special aspects such as computer memory in investigating large sets of complex networks. Intended for computer scientists, statisticians and mathematicians interested in the big data and networks, Big Data of Complex Networks is also a valuable tool for researchers in the fields of visualization, data analysis, computer vision and bioinformatics. Key features: Provides a complete discussion of both the hardware and software used to organize big data Describes a wide range of useful applications for managing big data and resultant data sets Maintains a firm focus on massive data and large networks Unveils innovative techniques to help readers handle big data Matthias Dehmer received his PhD in computer science from the Darmstadt University of Technology, Germany. Currently, he is Professor at UMIT – The Health and Life Sciences University, Austria, and the Universität der Bundeswehr München. His research interests are in graph theory, data science, complex networks, complexity, statistics and information theory. Frank Emmert-Streib received his PhD in theoretical physics from the University of Bremen, and is currently Associate professor at Tampere University of Technology, Finland. His research interests are in the field of computational biology, machine learning and network medicine. Stefan Pickl holds a PhD in mathematics from the Darmstadt University of Technology, and is currently a Professor at Bundeswehr Universität München. His research interests are in operations research, systems biology, graph theory and discrete optimization. Andreas Holzinger received his PhD in cognitive science from Graz University and his habilitation (second PhD) in computer science from Graz University of Technology. He is head of the Holzinger Group HCI-KDD at the Medical University Graz and Visiting Professor for Machine Learning in Health Informatics Vienna University of Technology.

Enterprise Big Data Engineering, Analytics, and Management

Author : Atzmueller, Martin
Publisher : IGI Global
ISBN 13 : 1522502947
Total Pages : 293 pages
Book Rating : 4.5/5 (225 download)

DOWNLOAD NOW!

Book Synopsis Enterprise Big Data Engineering, Analytics, and Management by : Atzmueller, Martin

Download or read book Enterprise Big Data Engineering, Analytics, and Management written by Atzmueller, Martin and published by IGI Global. This book was released on 2016-06-01 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: The significance of big data can be observed in any decision-making process as it is often used for forecasting and predictive analytics. Additionally, big data can be used to build a holistic view of an enterprise through a collection and analysis of large data sets retrospectively. As the data deluge deepens, new methods for analyzing, comprehending, and making use of big data become necessary. Enterprise Big Data Engineering, Analytics, and Management presents novel methodologies and practical approaches to engineering, managing, and analyzing large-scale data sets with a focus on enterprise applications and implementation. Featuring essential big data concepts including data mining, artificial intelligence, and information extraction, this publication provides a platform for retargeting the current research available in the field. Data analysts, IT professionals, researchers, and graduate-level students will find the timely research presented in this publication essential to furthering their knowledge in the field.

Large-Scale Graph Processing Using Apache Giraph

Author : Sherif Sakr
Publisher : Springer
ISBN 13 : 3319474316
Total Pages : 214 pages
Book Rating : 4.3/5 (194 download)

DOWNLOAD NOW!

Book Synopsis Large-Scale Graph Processing Using Apache Giraph by : Sherif Sakr

Download or read book Large-Scale Graph Processing Using Apache Giraph written by Sherif Sakr and published by Springer. This book was released on 2017-01-05 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book takes its reader on a journey through Apache Giraph, a popular distributed graph processing platform designed to bring the power of big data processing to graph data. Designed as a step-by-step self-study guide for everyone interested in large-scale graph processing, it describes the fundamental abstractions of the system, its programming models and various techniques for using the system to process graph data at scale, including the implementation of several popular and advanced graph analytics algorithms. The book is organized as follows: Chapter 1 starts by providing a general background of the big data phenomenon and a general introduction to the Apache Giraph system, its abstraction, programming model and design architecture. Next, chapter 2 focuses on Giraph as a platform and how to use it. Based on a sample job, even more advanced topics like monitoring the Giraph application lifecycle and different methods for monitoring Giraph jobs are explained. Chapter 3 then provides an introduction to Giraph programming, introduces the basic Giraph graph model and explains how to write Giraph programs. In turn, Chapter 4 discusses in detail the implementation of some popular graph algorithms including PageRank, connected components, shortest paths and triangle closing. Chapter 5 focuses on advanced Giraph programming, discussing common Giraph algorithmic optimizations, tunable Giraph configurations that determine the system’s utilization of the underlying resources, and how to write a custom graph input and output format. Lastly, chapter 6 highlights two systems that have been introduced to tackle the challenge of large scale graph processing, GraphX and GraphLab, and explains the main commonalities and differences between these systems and Apache Giraph. This book serves as an essential reference guide for students, researchers and practitioners in the domain of large scale graph processing. It offers step-by-step guidance, with several code examples and the complete source code available in the related github repository. Students will find a comprehensive introduction to and hands-on practice with tackling large scale graph processing problems using the Apache Giraph system, while researchers will discover thorough coverage of the emerging and ongoing advancements in big graph processing systems.

Data Mining in Large Sets of Complex Data

Author : Robson Leonardo Ferreira Cordeiro
Publisher : Springer Science & Business Media
ISBN 13 : 1447148908
Total Pages : 124 pages
Book Rating : 4.4/5 (471 download)

DOWNLOAD NOW!

Book Synopsis Data Mining in Large Sets of Complex Data by : Robson Leonardo Ferreira Cordeiro

Download or read book Data Mining in Large Sets of Complex Data written by Robson Leonardo Ferreira Cordeiro and published by Springer Science & Business Media. This book was released on 2013-01-11 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt: The amount and the complexity of the data gathered by current enterprises are increasing at an exponential rate. Consequently, the analysis of Big Data is nowadays a central challenge in Computer Science, especially for complex data. For example, given a satellite image database containing tens of Terabytes, how can we find regions aiming at identifying native rainforests, deforestation or reforestation? Can it be made automatically? Based on the work discussed in this book, the answers to both questions are a sound “yes”, and the results can be obtained in just minutes. In fact, results that used to require days or weeks of hard work from human specialists can now be obtained in minutes with high precision. Data Mining in Large Sets of Complex Data discusses new algorithms that take steps forward from traditional data mining (especially for clustering) by considering large, complex datasets. Usually, other works focus in one aspect, either data size or complexity. This work considers both: it enables mining complex data from high impact applications, such as breast cancer diagnosis, region classification in satellite images, assistance to climate change forecast, recommendation systems for the Web and social networks; the data are large in the Terabyte-scale, not in Giga as usual; and very accurate results are found in just minutes. Thus, it provides a crucial and well timed contribution for allowing the creation of real time applications that deal with Big Data of high complexity in which mining on the fly can make an immeasurable difference, such as supporting cancer diagnosis or detecting deforestation.

Graph Data Management

Author : George Fletcher
Publisher : Springer
ISBN 13 : 3319961934
Total Pages : 196 pages
Book Rating : 4.3/5 (199 download)

DOWNLOAD NOW!

Book Synopsis Graph Data Management by : George Fletcher

Download or read book Graph Data Management written by George Fletcher and published by Springer. This book was released on 2018-10-31 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a comprehensive overview of fundamental issues and recent advances in graph data management. Its aim is to provide beginning researchers in the area of graph data management, or in fields that require graph data management, an overview of the latest developments in this area, both in applied and in fundamental subdomains. The topics covered range from a general introduction to graph data management, to more specialized topics like graph visualization, flexible queries of graph data, parallel processing, and benchmarking. The book will help researchers put their work in perspective and show them which types of tools, techniques and technologies are available, which ones could best suit their needs, and where there are still open issues and future research directions. The chapters are contributed by leading experts in the relevant areas, presenting a coherent overview of the state of the art in the field. Readers should have a basic knowledge of data management techniques as they are taught in computer science MSc programs.

Data Management in Grid and Peer-to-Peer Systems

Author : Abdelkader Hameurlain
Publisher : Springer Science & Business Media
ISBN 13 : 3642229468
Total Pages : 144 pages
Book Rating : 4.6/5 (422 download)

DOWNLOAD NOW!

Book Synopsis Data Management in Grid and Peer-to-Peer Systems by : Abdelkader Hameurlain

Download or read book Data Management in Grid and Peer-to-Peer Systems written by Abdelkader Hameurlain and published by Springer Science & Business Media. This book was released on 2011-08-19 with total page 144 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 4th International Conference on Data Management in Grid and Peer-to-Peer Systems, Globe 2011, held in Toulouse, France, in September 2011 in conjunction with DEXA 2011. The 12 revised full papers presented were carefully reviewed and selected from 18 submissions. The papers are organized in topical sections on data storage and replication, semantics for P2P systems and performance evaluation, resource discovery and routing in mobile P2P networks, and data stream systems and large-scale distributed applications.

Knowledge Graphs and Big Data Processing

Author : Valentina Janev
Publisher : Springer Nature
ISBN 13 : 3030531996
Total Pages : 212 pages
Book Rating : 4.0/5 (35 download)

DOWNLOAD NOW!

Book Synopsis Knowledge Graphs and Big Data Processing by : Valentina Janev

Download or read book Knowledge Graphs and Big Data Processing written by Valentina Janev and published by Springer Nature. This book was released on 2020-07-15 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book is part of the LAMBDA Project (Learning, Applying, Multiplying Big Data Analytics), funded by the European Union, GA No. 809965. Data Analytics involves applying algorithmic processes to derive insights. Nowadays it is used in many industries to allow organizations and companies to make better decisions as well as to verify or disprove existing theories or models. The term data analytics is often used interchangeably with intelligence, statistics, reasoning, data mining, knowledge discovery, and others. The goal of this book is to introduce some of the definitions, methods, tools, frameworks, and solutions for big data processing, starting from the process of information extraction and knowledge representation, via knowledge processing and analytics to visualization, sense-making, and practical applications. Each chapter in this book addresses some pertinent aspect of the data processing chain, with a specific focus on understanding Enterprise Knowledge Graphs, Semantic Big Data Architectures, and Smart Data Analytics solutions. This book is addressed to graduate students from technical disciplines, to professional audiences following continuous education short courses, and to researchers from diverse areas following self-study courses. Basic skills in computer science, mathematics, and statistics are required.

Large-Scale Data Analytics

Author : Aris Gkoulalas-Divanis
Publisher : Springer Science & Business Media
ISBN 13 : 1461492424
Total Pages : 276 pages
Book Rating : 4.4/5 (614 download)

DOWNLOAD NOW!

Book Synopsis Large-Scale Data Analytics by : Aris Gkoulalas-Divanis

Download or read book Large-Scale Data Analytics written by Aris Gkoulalas-Divanis and published by Springer Science & Business Media. This book was released on 2014-01-08 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited book collects state-of-the-art research related to large-scale data analytics that has been accomplished over the last few years. This is among the first books devoted to this important area based on contributions from diverse scientific areas such as databases, data mining, supercomputing, hardware architecture, data visualization, statistics, and privacy. There is increasing need for new approaches and technologies that can analyze and synthesize very large amounts of data, in the order of petabytes, that are generated by massively distributed data sources. This requires new distributed architectures for data analysis. Additionally, the heterogeneity of such sources imposes significant challenges for the efficient analysis of the data under numerous constraints, including consistent data integration, data homogenization and scaling, privacy and security preservation. The authors also broaden reader understanding of emerging real-world applications in domains such as customer behavior modeling, graph mining, telecommunications, cyber-security, and social network analysis, all of which impose extra requirements for large-scale data analysis. Large-Scale Data Analytics is organized in 8 chapters, each providing a survey of an important direction of large-scale data analytics or individual results of the emerging research in the field. The book presents key recent research that will help shape the future of large-scale data analytics, leading the way to the design of new approaches and technologies that can analyze and synthesize very large amounts of heterogeneous data. Students, researchers, professionals and practitioners will find this book an authoritative and comprehensive resource.

Toward Sustainable And Economic Smart Mobility: Shaping The Future Of Smart Cities

Author : Mahmoud Hashem Eiza
Publisher : World Scientific
ISBN 13 : 1786347873
Total Pages : 212 pages
Book Rating : 4.7/5 (863 download)

DOWNLOAD NOW!

Book Synopsis Toward Sustainable And Economic Smart Mobility: Shaping The Future Of Smart Cities by : Mahmoud Hashem Eiza

Download or read book Toward Sustainable And Economic Smart Mobility: Shaping The Future Of Smart Cities written by Mahmoud Hashem Eiza and published by World Scientific. This book was released on 2020-06-18 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: During the last decade, developments in smart cars, mobile devices, internet of things and vehicular communications are revolutionizing the future of smart cities. With the rapid integration of these smart devices into our surroundings, we are heading to a new era of a highly connected and environmentally friendly ecosystem.This book offers a unique opportunity for the reader to explore state-of-the-art developments in applications, technologies (e.g., Big Data and artificial intelligence), services and research trends in smart mobility for smart cities. It also provides a reference for professionals and researchers in the areas of smart mobility (e.g., autonomous valet parking, passenger trajectory data, smart traffic control systems) and recent technical trends on their enabling technologies. The materials have been carefully selected to reflect the latest developments in the field with many novel contributions from academics and industry experts from around the world.

Big Data

Author : Rajkumar Buyya
Publisher : Morgan Kaufmann
ISBN 13 : 0128093463
Total Pages : 496 pages
Book Rating : 4.1/5 (28 download)

DOWNLOAD NOW!

Book Synopsis Big Data by : Rajkumar Buyya

Download or read book Big Data written by Rajkumar Buyya and published by Morgan Kaufmann. This book was released on 2016-06-07 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data: Principles and Paradigms captures the state-of-the-art research on the architectural aspects, technologies, and applications of Big Data. The book identifies potential future directions and technologies that facilitate insight into numerous scientific, business, and consumer applications. To help realize Big Data's full potential, the book addresses numerous challenges, offering the conceptual and technological solutions for tackling them. These challenges include life-cycle data management, large-scale storage, flexible processing infrastructure, data modeling, scalable machine learning, data analysis algorithms, sampling techniques, and privacy and ethical issues. - Covers computational platforms supporting Big Data applications - Addresses key principles underlying Big Data computing - Examines key developments supporting next generation Big Data platforms - Explores the challenges in Big Data computing and ways to overcome them - Contains expert contributors from both academia and industry

Advances in Machine Learning for Big Data Analysis

Author : Satchidananda Dehuri
Publisher : Springer Nature
ISBN 13 : 981168930X
Total Pages : 254 pages
Book Rating : 4.8/5 (116 download)

DOWNLOAD NOW!

Book Synopsis Advances in Machine Learning for Big Data Analysis by : Satchidananda Dehuri

Download or read book Advances in Machine Learning for Big Data Analysis written by Satchidananda Dehuri and published by Springer Nature. This book was released on 2022-02-24 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on research aspects of ensemble approaches of machine learning techniques that can be applied to address the big data problems. In this book, various advancements of machine learning algorithms to extract data-driven decisions from big data in diverse domains such as the banking sector, healthcare, social media, and video surveillance are presented in several chapters. Each of them has separate functionalities, which can be leveraged to solve a specific set of big data applications. This book is a potential resource for various advances in the field of machine learning and data science to solve big data problems with many objectives. It has been observed from the literature that several works have been focused on the advancement of machine learning in various fields like biomedical, stock prediction, sentiment analysis, etc. However, limited discussions have been carried out on application of advanced machine learning techniques in solving big data problems.

Big Data Analytics and Knowledge Discovery

Author : Carlos Ordonez
Publisher : Springer
ISBN 13 : 3319985396
Total Pages : 401 pages
Book Rating : 4.3/5 (199 download)

DOWNLOAD NOW!

Book Synopsis Big Data Analytics and Knowledge Discovery by : Carlos Ordonez

Download or read book Big Data Analytics and Knowledge Discovery written by Carlos Ordonez and published by Springer. This book was released on 2018-08-20 with total page 401 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 20th International Conference on Big Data Analytics and Knowledge Discovery, DaWaK 2018, held in Regensburg, Germany, in September 2018. The 13 revised full papers and 17 short papers presented were carefully reviewed and selected from 76 submissions. The papers are organized in the following topical sections: Graph analytics; case studies; classification and clustering; pre-processing; sequences; cloud and database systems; and data mining.

Smart Infrastructure and Applications

Author : Rashid Mehmood
Publisher : Springer
ISBN 13 : 3030137058
Total Pages : 667 pages
Book Rating : 4.0/5 (31 download)

DOWNLOAD NOW!

Book Synopsis Smart Infrastructure and Applications by : Rashid Mehmood

Download or read book Smart Infrastructure and Applications written by Rashid Mehmood and published by Springer. This book was released on 2019-06-20 with total page 667 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a multidisciplinary view of smart infrastructure through a range of diverse introductory and advanced topics. The book features an array of subjects that include: smart cities and infrastructure, e-healthcare, emergency and disaster management, Internet of Vehicles, supply chain management, eGovernance, and high performance computing. The book is divided into five parts: Smart Transportation, Smart Healthcare, Miscellaneous Applications, Big Data and High Performance Computing, and Internet of Things (IoT). Contributions are from academics, researchers, and industry professionals around the world. Features a broad mix of topics related to smart infrastructure and smart applications, particularly high performance computing, big data, and artificial intelligence; Includes a strong emphasis on methodological aspects of infrastructure, technology and application development; Presents a substantial overview of research and development on key economic sectors including healthcare and transportation.

Euro-Par 2013: Parallel Processing Workshops

Author : Dieter an Mey
Publisher : Springer
ISBN 13 : 3642544207
Total Pages : 928 pages
Book Rating : 4.6/5 (425 download)

DOWNLOAD NOW!

Book Synopsis Euro-Par 2013: Parallel Processing Workshops by : Dieter an Mey

Download or read book Euro-Par 2013: Parallel Processing Workshops written by Dieter an Mey and published by Springer. This book was released on 2014-04-10 with total page 928 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes thoroughly refereed post-conference proceedings of the workshops of the 19th International Conference on Parallel Computing, Euro-Par 2013, held in Aachen, Germany in August 2013. The 99 papers presented were carefully reviewed and selected from 145 submissions. The papers include seven workshops that have been co-located with Euro-Par in the previous years: - Big Data Cloud (Second Workshop on Big Data Management in Clouds) - Hetero Par (11th Workshop on Algorithms, Models and Tools for Parallel Computing on Heterogeneous Platforms) - HiBB (Fourth Workshop on High Performance Bioinformatics and Biomedicine) - OMHI (Second Workshop on On-chip Memory Hierarchies and Interconnects) - PROPER (Sixth Workshop on Productivity and Performance) - Resilience (Sixth Workshop on Resiliency in High Performance Computing with Clusters, Clouds, and Grids) - UCHPC (Sixth Workshop on Un Conventional High Performance Computing) as well as six newcomers: - DIHC (First Workshop on Dependability and Interoperability in Heterogeneous Clouds) - Fed ICI (First Workshop on Federative and Interoperable Cloud Infrastructures) - LSDVE (First Workshop on Large Scale Distributed Virtual Environments on Clouds and P2P) - MHPC (Workshop on Middleware for HPC and Big Data Systems) -PADABS ( First Workshop on Parallel and Distributed Agent Based Simulations) - ROME (First Workshop on Runtime and Operating Systems for the Many core Era) All these workshops focus on promotion and advancement of all aspects of parallel and distributed computing.

Encyclopedia of Business Analytics and Optimization

Author : Wang, John
Publisher : IGI Global
ISBN 13 : 1466652039
Total Pages : 2862 pages
Book Rating : 4.4/5 (666 download)

DOWNLOAD NOW!

Book Synopsis Encyclopedia of Business Analytics and Optimization by : Wang, John

Download or read book Encyclopedia of Business Analytics and Optimization written by Wang, John and published by IGI Global. This book was released on 2014-02-28 with total page 2862 pages. Available in PDF, EPUB and Kindle. Book excerpt: As the age of Big Data emerges, it becomes necessary to take the five dimensions of Big Data- volume, variety, velocity, volatility, and veracity- and focus these dimensions towards one critical emphasis - value. The Encyclopedia of Business Analytics and Optimization confronts the challenges of information retrieval in the age of Big Data by exploring recent advances in the areas of knowledge management, data visualization, interdisciplinary communication, and others. Through its critical approach and practical application, this book will be a must-have reference for any professional, leader, analyst, or manager interested in making the most of the knowledge resources at their disposal.