Big Data Management And Processing

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Big Data Management and Processing

Author : Kuan-Ching Li
Publisher : CRC Press
ISBN 13 : 1498768083
Total Pages : 489 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis Big Data Management and Processing by : Kuan-Ching Li

Download or read book Big Data Management and Processing written by Kuan-Ching Li and published by CRC Press. This book was released on 2017-05-19 with total page 489 pages. Available in PDF, EPUB and Kindle. Book excerpt: From the Foreword: "Big Data Management and Processing is [a] state-of-the-art book that deals with a wide range of topical themes in the field of Big Data. The book, which probes many issues related to this exciting and rapidly growing field, covers processing, management, analytics, and applications... [It] is a very valuable addition to the literature. It will serve as a source of up-to-date research in this continuously developing area. The book also provides an opportunity for researchers to explore the use of advanced computing technologies and their impact on enhancing our capabilities to conduct more sophisticated studies." ---Sartaj Sahni, University of Florida, USA "Big Data Management and Processing covers the latest Big Data research results in processing, analytics, management and applications. Both fundamental insights and representative applications are provided. This book is a timely and valuable resource for students, researchers and seasoned practitioners in Big Data fields. --Hai Jin, Huazhong University of Science and Technology, China Big Data Management and Processing explores a range of big data related issues and their impact on the design of new computing systems. The twenty-one chapters were carefully selected and feature contributions from several outstanding researchers. The book endeavors to strike a balance between theoretical and practical coverage of innovative problem solving techniques for a range of platforms. It serves as a repository of paradigms, technologies, and applications that target different facets of big data computing systems. The first part of the book explores energy and resource management issues, as well as legal compliance and quality management for Big Data. It covers In-Memory computing and In-Memory data grids, as well as co-scheduling for high performance computing applications. The second part of the book includes comprehensive coverage of Hadoop and Spark, along with security, privacy, and trust challenges and solutions. The latter part of the book covers mining and clustering in Big Data, and includes applications in genomics, hospital big data processing, and vehicular cloud computing. The book also analyzes funding for Big Data projects.

Large Scale and Big Data

Author : Sherif Sakr
Publisher : CRC Press
ISBN 13 : 1466581506
Total Pages : 640 pages
Book Rating : 4.4/5 (665 download)

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Book Synopsis Large Scale and Big Data by : Sherif Sakr

Download or read book Large Scale and Big Data written by Sherif Sakr and published by CRC Press. This book was released on 2014-06-25 with total page 640 pages. Available in PDF, EPUB and Kindle. Book excerpt: Large Scale and Big Data: Processing and Management provides readers with a central source of reference on the data management techniques currently available for large-scale data processing. Presenting chapters written by leading researchers, academics, and practitioners, it addresses the fundamental challenges associated with Big Data processing tools and techniques across a range of computing environments. The book begins by discussing the basic concepts and tools of large-scale Big Data processing and cloud computing. It also provides an overview of different programming models and cloud-based deployment models. The book’s second section examines the usage of advanced Big Data processing techniques in different domains, including semantic web, graph processing, and stream processing. The third section discusses advanced topics of Big Data processing such as consistency management, privacy, and security. Supplying a comprehensive summary from both the research and applied perspectives, the book covers recent research discoveries and applications, making it an ideal reference for a wide range of audiences, including researchers and academics working on databases, data mining, and web scale data processing. After reading this book, you will gain a fundamental understanding of how to use Big Data-processing tools and techniques effectively across application domains. Coverage includes cloud data management architectures, big data analytics visualization, data management, analytics for vast amounts of unstructured data, clustering, classification, link analysis of big data, scalable data mining, and machine learning techniques.

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)

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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.

Big Data Management

Author : Fausto Pedro García Márquez
Publisher : Springer
ISBN 13 : 3319454986
Total Pages : 267 pages
Book Rating : 4.3/5 (194 download)

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Book Synopsis Big Data Management by : Fausto Pedro García Márquez

Download or read book Big Data Management written by Fausto Pedro García Márquez and published by Springer. This book was released on 2016-11-15 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the analytic principles of business practice and big data. Specifically, it provides an interface between the main disciplines of engineering/technology and the organizational and administrative aspects of management, serving as a complement to books in other disciplines such as economics, finance, marketing and risk analysis. The contributors present their areas of expertise, together with essential case studies that illustrate the successful application of engineering management theories in real-life examples.

Big Data Management

Author : Peter Ghavami
Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 3110664321
Total Pages : 180 pages
Book Rating : 4.1/5 (16 download)

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Book Synopsis Big Data Management by : Peter Ghavami

Download or read book Big Data Management written by Peter Ghavami and published by Walter de Gruyter GmbH & Co KG. This book was released on 2020-11-09 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data analytics is core to business and decision making. The rapid increase in data volume, velocity and variety offers both opportunities and challenges. While open source solutions to store big data, like Hadoop, offer platforms for exploring value and insight from big data, they were not originally developed with data security and governance in mind. Big Data Management discusses numerous policies, strategies and recipes for managing big data. It addresses data security, privacy, controls and life cycle management offering modern principles and open source architectures for successful governance of big data. The author has collected best practices from the world’s leading organizations that have successfully implemented big data platforms. The topics discussed cover the entire data management life cycle, data quality, data stewardship, regulatory considerations, data council, architectural and operational models are presented for successful management of big data. The book is a must-read for data scientists, data engineers and corporate leaders who are implementing big data platforms in their organizations.

High-Performance Big Data Computing

Author : Dhabaleswar K. Panda
Publisher : MIT Press
ISBN 13 : 0262369427
Total Pages : 275 pages
Book Rating : 4.2/5 (623 download)

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Book Synopsis High-Performance Big Data Computing by : Dhabaleswar K. Panda

Download or read book High-Performance Big Data Computing written by Dhabaleswar K. Panda and published by MIT Press. This book was released on 2022-08-02 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: An in-depth overview of an emerging field that brings together high-performance computing, big data processing, and deep lLearning. Over the last decade, the exponential explosion of data known as big data has changed the way we understand and harness the power of data. The emerging field of high-performance big data computing, which brings together high-performance computing (HPC), big data processing, and deep learning, aims to meet the challenges posed by large-scale data processing. This book offers an in-depth overview of high-performance big data computing and the associated technical issues, approaches, and solutions. The book covers basic concepts and necessary background knowledge, including data processing frameworks, storage systems, and hardware capabilities; offers a detailed discussion of technical issues in accelerating big data computing in terms of computation, communication, memory and storage, codesign, workload characterization and benchmarking, and system deployment and management; and surveys benchmarks and workloads for evaluating big data middleware systems. It presents a detailed discussion of big data computing systems and applications with high-performance networking, computing, and storage technologies, including state-of-the-art designs for data processing and storage systems. Finally, the book considers some advanced research topics in high-performance big data computing, including designing high-performance deep learning over big data (DLoBD) stacks and HPC cloud technologies.

Guidebook for Managing Data from Emerging Technologies for Transportation

Author : Kelley Klaver Pecheux
Publisher :
ISBN 13 : 9780309673495
Total Pages : 107 pages
Book Rating : 4.6/5 (734 download)

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Book Synopsis Guidebook for Managing Data from Emerging Technologies for Transportation by : Kelley Klaver Pecheux

Download or read book Guidebook for Managing Data from Emerging Technologies for Transportation written by Kelley Klaver Pecheux and published by . This book was released on 2020 with total page 107 pages. Available in PDF, EPUB and Kindle. Book excerpt: With increased connectivity between vehicles, sensors, systems, shared-use transportation, and mobile devices, unexpected and unparalleled amounts of data are being added to the transportation domain at a rapid rate, and these data are too large, too varied in nature, and will change too quickly to be handled by the traditional database management systems of most transportation agencies. The TRB National Cooperative Highway Research Program's NCHRP Research Report 952: Guidebook for Managing Data from Emerging Technologies for Transportation provides guidance, tools, and a big data management framework, and it lays out a roadmap for transportation agencies on how they can begin to shift - technically, institutionally, and culturally - toward effectively managing data from emerging technologies. Modern, flexible, and scalable "big data" methods to manage these data need to be adopted by transportation agencies if the data are to be used to facilitate better decision-making. As many agencies are already forced to do more with less while meeting higher public expectations, continuing with traditional data management systems and practices will prove costly for agencies unable to shift.

New Horizons for a Data-Driven Economy

Author : José María Cavanillas
Publisher : Springer
ISBN 13 : 3319215698
Total Pages : 303 pages
Book Rating : 4.3/5 (192 download)

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Book Synopsis New Horizons for a Data-Driven Economy by : José María Cavanillas

Download or read book New Horizons for a Data-Driven Economy written by José María Cavanillas and published by Springer. This book was released on 2016-04-04 with total page 303 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book readers will find technological discussions on the existing and emerging technologies across the different stages of the big data value chain. They will learn about legal aspects of big data, the social impact, and about education needs and requirements. And they will discover the business perspective and how big data technology can be exploited to deliver value within different sectors of the economy. The book is structured in four parts: Part I “The Big Data Opportunity” explores the value potential of big data with a particular focus on the European context. It also describes the legal, business and social dimensions that need to be addressed, and briefly introduces the European Commission’s BIG project. Part II “The Big Data Value Chain” details the complete big data lifecycle from a technical point of view, ranging from data acquisition, analysis, curation and storage, to data usage and exploitation. Next, Part III “Usage and Exploitation of Big Data” illustrates the value creation possibilities of big data applications in various sectors, including industry, healthcare, finance, energy, media and public services. Finally, Part IV “A Roadmap for Big Data Research” identifies and prioritizes the cross-sectorial requirements for big data research, and outlines the most urgent and challenging technological, economic, political and societal issues for big data in Europe. This compendium summarizes more than two years of work performed by a leading group of major European research centers and industries in the context of the BIG project. It brings together research findings, forecasts and estimates related to this challenging technological context that is becoming the major axis of the new digitally transformed business environment.

Big Data and Analytics

Author : Vincenzo Morabito
Publisher : Springer
ISBN 13 : 3319106651
Total Pages : 183 pages
Book Rating : 4.3/5 (191 download)

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Book Synopsis Big Data and Analytics by : Vincenzo Morabito

Download or read book Big Data and Analytics written by Vincenzo Morabito and published by Springer. This book was released on 2015-01-31 with total page 183 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents and discusses the main strategic and organizational challenges posed by Big Data and analytics in a manner relevant to both practitioners and scholars. The first part of the book analyzes strategic issues relating to the growing relevance of Big Data and analytics for competitive advantage, which is also attributable to empowerment of activities such as consumer profiling, market segmentation, and development of new products or services. Detailed consideration is also given to the strategic impact of Big Data and analytics on innovation in domains such as government and education and to Big Data-driven business models. The second part of the book addresses the impact of Big Data and analytics on management and organizations, focusing on challenges for governance, evaluation, and change management, while the concluding part reviews real examples of Big Data and analytics innovation at the global level. The text is supported by informative illustrations and case studies, so that practitioners can use the book as a toolbox to improve understanding and exploit business opportunities related to Big Data and analytics.

Data Stream Management

Author : Minos Garofalakis
Publisher : Springer
ISBN 13 : 354028608X
Total Pages : 537 pages
Book Rating : 4.5/5 (42 download)

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Book Synopsis Data Stream Management by : Minos Garofalakis

Download or read book Data Stream Management written by Minos Garofalakis and published by Springer. This book was released on 2016-07-11 with total page 537 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume focuses on the theory and practice of data stream management, and the novel challenges this emerging domain poses for data-management algorithms, systems, and applications. The collection of chapters, contributed by authorities in the field, offers a comprehensive introduction to both the algorithmic/theoretical foundations of data streams, as well as the streaming systems and applications built in different domains. A short introductory chapter provides a brief summary of some basic data streaming concepts and models, and discusses the key elements of a generic stream query processing architecture. Subsequently, Part I focuses on basic streaming algorithms for some key analytics functions (e.g., quantiles, norms, join aggregates, heavy hitters) over streaming data. Part II then examines important techniques for basic stream mining tasks (e.g., clustering, classification, frequent itemsets). Part III discusses a number of advanced topics on stream processing algorithms, and Part IV focuses on system and language aspects of data stream processing with surveys of influential system prototypes and language designs. Part V then presents some representative applications of streaming techniques in different domains (e.g., network management, financial analytics). Finally, the volume concludes with an overview of current data streaming products and new application domains (e.g. cloud computing, big data analytics, and complex event processing), and a discussion of future directions in this exciting field. The book provides a comprehensive overview of core concepts and technological foundations, as well as various systems and applications, and is of particular interest to students, lecturers and researchers in the area of data stream management.

Big Data

Author : James Warren
Publisher : Simon and Schuster
ISBN 13 : 1638351104
Total Pages : 481 pages
Book Rating : 4.6/5 (383 download)

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Book Synopsis Big Data by : James Warren

Download or read book Big Data written by James Warren and published by Simon and Schuster. This book was released on 2015-04-29 with total page 481 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Big Data teaches you to build big data systems using an architecture that takes advantage of clustered hardware along with new tools designed specifically to capture and analyze web-scale data. It describes a scalable, easy-to-understand approach to big data systems that can be built and run by a small team. Following a realistic example, this book guides readers through the theory of big data systems, how to implement them in practice, and how to deploy and operate them once they're built. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Book Web-scale applications like social networks, real-time analytics, or e-commerce sites deal with a lot of data, whose volume and velocity exceed the limits of traditional database systems. These applications require architectures built around clusters of machines to store and process data of any size, or speed. Fortunately, scale and simplicity are not mutually exclusive. Big Data teaches you to build big data systems using an architecture designed specifically to capture and analyze web-scale data. This book presents the Lambda Architecture, a scalable, easy-to-understand approach that can be built and run by a small team. You'll explore the theory of big data systems and how to implement them in practice. In addition to discovering a general framework for processing big data, you'll learn specific technologies like Hadoop, Storm, and NoSQL databases. This book requires no previous exposure to large-scale data analysis or NoSQL tools. Familiarity with traditional databases is helpful. What's Inside Introduction to big data systems Real-time processing of web-scale data Tools like Hadoop, Cassandra, and Storm Extensions to traditional database skills About the Authors Nathan Marz is the creator of Apache Storm and the originator of the Lambda Architecture for big data systems. James Warren is an analytics architect with a background in machine learning and scientific computing. Table of Contents A new paradigm for Big Data PART 1 BATCH LAYER Data model for Big Data Data model for Big Data: Illustration Data storage on the batch layer Data storage on the batch layer: Illustration Batch layer Batch layer: Illustration An example batch layer: Architecture and algorithms An example batch layer: Implementation PART 2 SERVING LAYER Serving layer Serving layer: Illustration PART 3 SPEED LAYER Realtime views Realtime views: Illustration Queuing and stream processing Queuing and stream processing: Illustration Micro-batch stream processing Micro-batch stream processing: Illustration Lambda Architecture in depth

Big Data

Author : Balamurugan Balusamy
Publisher : John Wiley & Sons
ISBN 13 : 1119701872
Total Pages : 368 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Big Data by : Balamurugan Balusamy

Download or read book Big Data written by Balamurugan Balusamy and published by John Wiley & Sons. This book was released on 2021-03-15 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn Big Data from the ground up with this complete and up-to-date resource from leaders in the field Big Data: Concepts, Technology, and Architecture delivers a comprehensive treatment of Big Data tools, terminology, and technology perfectly suited to a wide range of business professionals, academic researchers, and students. Beginning with a fulsome overview of what we mean when we say, “Big Data,” the book moves on to discuss every stage of the lifecycle of Big Data. You’ll learn about the creation of structured, unstructured, and semi-structured data, data storage solutions, traditional database solutions like SQL, data processing, data analytics, machine learning, and data mining. You’ll also discover how specific technologies like Apache Hadoop, SQOOP, and Flume work. Big Data also covers the central topic of big data visualization with Tableau, and you’ll learn how to create scatter plots, histograms, bar, line, and pie charts with that software. Accessibly organized, Big Data includes illuminating case studies throughout the material, showing you how the included concepts have been applied in real-world settings. Some of those concepts include: The common challenges facing big data technology and technologists, like data heterogeneity and incompleteness, data volume and velocity, storage limitations, and privacy concerns Relational and non-relational databases, like RDBMS, NoSQL, and NewSQL databases Virtualizing Big Data through encapsulation, partitioning, and isolating, as well as big data server virtualization Apache software, including Hadoop, Cassandra, Avro, Pig, Mahout, Oozie, and Hive The Big Data analytics lifecycle, including business case evaluation, data preparation, extraction, transformation, analysis, and visualization Perfect for data scientists, data engineers, and database managers, Big Data also belongs on the bookshelves of business intelligence analysts who are required to make decisions based on large volumes of information. Executives and managers who lead teams responsible for keeping or understanding large datasets will also benefit from this book.

Management Decision-Making, Big Data and Analytics

Author : Simone Gressel
Publisher : SAGE
ISBN 13 : 1529738288
Total Pages : 354 pages
Book Rating : 4.5/5 (297 download)

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Book Synopsis Management Decision-Making, Big Data and Analytics by : Simone Gressel

Download or read book Management Decision-Making, Big Data and Analytics written by Simone Gressel and published by SAGE. This book was released on 2020-10-12 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: Accessible and concise, this exciting new textbook examines data analytics from a managerial and organizational perspective and looks at how they can help managers become more effective decision-makers. The book successfully combines theory with practical application, featuring case studies, examples and a ‘critical incidents’ feature that make these topics engaging and relevant for students of business and management. The book features chapters on cutting-edge topics, including: • Big data • Analytics • Managing emerging technologies and decision-making • Managing the ethics, security, privacy and legal aspects of data-driven decision-making The book is accompanied by an Instructor’s Manual, PowerPoint slides and access to journal articles. Suitable for management students studying business analytics and decision-making at undergraduate, postgraduate and MBA levels.

Big Data Analytics in Supply Chain Management

Author : Iman Rahimi
Publisher : CRC Press
ISBN 13 : 1000326918
Total Pages : 211 pages
Book Rating : 4.0/5 (3 download)

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Book Synopsis Big Data Analytics in Supply Chain Management by : Iman Rahimi

Download or read book Big Data Analytics in Supply Chain Management written by Iman Rahimi and published by CRC Press. This book was released on 2020-12-20 with total page 211 pages. Available in PDF, EPUB and Kindle. Book excerpt: In a world of soaring digitization, social media, financial transactions, and production and logistics processes constantly produce massive data. Employing analytical tools to extract insights and foresights from data improves the quality, speed, and reliability of solutions to highly intertwined issues faced in supply chain operations. From procurement in Industry 4.0 to sustainable consumption behavior to curriculum development for data scientists, this book offers a wide array of techniques and theories of Big Data Analytics applied to Supply Chain Management. It offers a comprehensive overview and forms a new synthesis by bringing together seemingly divergent fields of research. Intended for Engineering and Business students, scholars, and professionals, this book is a collection of state-of-the-art research and best practices to spur discussion about and extend the cumulant knowledge of emerging supply chain problems.

Managing and Processing Big Data in Cloud Computing

Author : Kannan, Rajkumar
Publisher : IGI Global
ISBN 13 : 1466697687
Total Pages : 307 pages
Book Rating : 4.4/5 (666 download)

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Book Synopsis Managing and Processing Big Data in Cloud Computing by : Kannan, Rajkumar

Download or read book Managing and Processing Big Data in Cloud Computing written by Kannan, Rajkumar and published by IGI Global. This book was released on 2016-01-07 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big data has presented a number of opportunities across industries. With these opportunities come a number of challenges associated with handling, analyzing, and storing large data sets. One solution to this challenge is cloud computing, which supports a massive storage and computation facility in order to accommodate big data processing. Managing and Processing Big Data in Cloud Computing explores the challenges of supporting big data processing and cloud-based platforms as a proposed solution. Emphasizing a number of crucial topics such as data analytics, wireless networks, mobile clouds, and machine learning, this publication meets the research needs of data analysts, IT professionals, researchers, graduate students, and educators in the areas of data science, computer programming, and IT development.

Big Data Driven Supply Chain Management

Author : Nada R. Sanders
Publisher : Pearson Education
ISBN 13 : 0133762823
Total Pages : 273 pages
Book Rating : 4.1/5 (337 download)

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Book Synopsis Big Data Driven Supply Chain Management by : Nada R. Sanders

Download or read book Big Data Driven Supply Chain Management written by Nada R. Sanders and published by Pearson Education. This book was released on 2014-05-07 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master a complete, five-step roadmap for leveraging Big Data and analytics to gain unprecedented competitive advantage from your supply chain. Using Big Data, pioneers such as Amazon, UPS, and Wal-Mart are gaining unprecedented mastery over their supply chains. They are achieving greater visibility into inventory levels, order fulfillment rates, material and product delivery… using predictive data analytics to match supply with demand; leveraging new planning strengths to optimize their sales channel strategies; optimizing supply chain strategy and competitive priorities; even launching powerful new ventures. Despite these opportunities, many supply chain operations are gaining limited or no value from Big Data. In Big Data Driven Supply Chain Management, Nada Sanders presents a systematic five-step framework for using Big Data in supply chains. You'll learn best practices for segmenting and analyzing customers, defining competitive priorities for each segment, aligning functions behind strategy, dissolving organizational boundaries to sense demand and make better decisions, and choose the right metrics to support all of this. Using these techniques, you can overcome the widespread obstacles to making the most of Big Data in your supply chain — and earn big profits from the data you're already generating. For all executives, managers, and analysts interested in using Big Data technologies to improve supply chain performance.

Big Data

Author : Kuan-Ching Li
Publisher : CRC Press
ISBN 13 : 1482240564
Total Pages : 498 pages
Book Rating : 4.4/5 (822 download)

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Book Synopsis Big Data by : Kuan-Ching Li

Download or read book Big Data written by Kuan-Ching Li and published by CRC Press. This book was released on 2015-02-23 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt: As today's organizations are capturing exponentially larger amounts of data than ever, now is the time for organizations to rethink how they digest that data. Through advanced algorithms and analytics techniques, organizations can harness this data, discover hidden patterns, and use the newly acquired knowledge to achieve competitive advantages.Pre