Information Management And Big Data
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| Author | : Peter Lake |
| Publisher | : Springer |
| Total Pages | : 304 |
| Release | : 2015-01-12 |
| Genre | : Business & Economics |
| ISBN | : 3319135031 |
This timely text/reference explores the business and technical issues involved in the management of information systems in the era of big data and beyond. Topics and features: presents review questions and discussion topics in each chapter for classroom group work and individual research assignments; discusses the potential use of a variety of big data tools and techniques in a business environment, explaining how these can fit within an information systems strategy; reviews existing theories and practices in information systems, and explores their continued relevance in the era of big data; describes the key technologies involved in information systems in general and big data in particular, placing these technologies in an historic context; suggests areas for further research in this fast moving domain; equips readers with an understanding of the important aspects of a data scientist’s job; provides hands-on experience to further assist in the understanding of the technologies involved.
| Author | : William McKnight |
| Publisher | : Newnes |
| Total Pages | : 214 |
| Release | : 2013-11-30 |
| Genre | : Computers |
| ISBN | : 0124095267 |
Information Management: Gaining a Competitive Advantage with Data is about making smart decisions to make the most of company information. Expert author William McKnight develops the value proposition for information in the enterprise and succinctly outlines the numerous forms of data storage. Information Management will enlighten you, challenge your preconceived notions, and help activate information in the enterprise. Get the big picture on managing data so that your team can make smart decisions by understanding how everything from workload allocation to data stores fits together. The practical, hands-on guidance in this book includes: Part 1: The importance of information management and analytics to business, and how data warehouses are used Part 2: The technologies and data that advance an organization, and extend data warehouses and related functionality Part 3: Big Data and NoSQL, and how technologies like Hadoop enable management of new forms of data Part 4: Pulls it all together, while addressing topics of agile development, modern business intelligence, and organizational change management Read the book cover-to-cover, or keep it within reach for a quick and useful resource. Either way, this book will enable you to master all of the possibilities for data or the broadest view across the enterprise. Balances business and technology, with non-product-specific technical detail Shows how to leverage data to deliver ROI for a business Engaging and approachable, with practical advice on the pros and cons of each domain, so that you learn how information fits together into a complete architecture Provides a path for the data warehouse professional into the new normal of heterogeneity, including NoSQL solutions
| Author | : Thomas Davenport |
| Publisher | : Harvard Business Review Press |
| Total Pages | : 241 |
| Release | : 2014-02-04 |
| Genre | : Business & Economics |
| ISBN | : 1422168174 |
Go ahead, be skeptical about big data. The author was—at first. When the term “big data” first came on the scene, bestselling author Tom Davenport (Competing on Analytics, Analytics at Work) thought it was just another example of technology hype. But his research in the years that followed changed his mind. Now, in clear, conversational language, Davenport explains what big data means—and why everyone in business needs to know about it. Big Data at Work covers all the bases: what big data means from a technical, consumer, and management perspective; what its opportunities and costs are; where it can have real business impact; and which aspects of this hot topic have been oversold. This book will help you understand: • Why big data is important to you and your organization • What technology you need to manage it • How big data could change your job, your company, and your industry • How to hire, rent, or develop the kinds of people who make big data work • The key success factors in implementing any big data project • How big data is leading to a new approach to managing analytics With dozens of company examples, including UPS, GE, Amazon, United Healthcare, Citigroup, and many others, this book will help you seize all opportunities—from improving decisions, products, and services to strengthening customer relationships. It will show you how to put big data to work in your own organization so that you too can harness the power of this ever-evolving new resource.
| Author | : Kuan-Ching Li |
| Publisher | : CRC Press |
| Total Pages | : 489 |
| Release | : 2017-05-19 |
| Genre | : Business & Economics |
| ISBN | : 1498768083 |
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.
| Author | : Joanna Paliszkiewicz |
| Publisher | : CRC Press |
| Total Pages | : 246 |
| Release | : 2020-06-18 |
| Genre | : Business & Economics |
| ISBN | : 1000093670 |
This book is a wonderful collection of chapters that posits how managers need to cope in the Big Data era. It highlights many of the emerging developments in technologies, applications, and trends related to management’s needs in this Big Data era. —Dr. Jay Liebowitz, Harrisburg University of Science and Technology This book presents some meaningful work on Big Data analytics and its applications. Each chapter generates helpful guidance to the readers on Big Data analytics and its applications, challenges, and prospects that is necessary for organizational strategic direction. —Dr. Alex Koohang, Middle Georgia State University Big Data is a concept that has caught the attention of practitioners, academicians, and researchers. Big Data offers organizations the possibility of gaining a competitive advantage by managing, collecting, and analyzing massive amounts of data. As the promises and challenges posed by Big Data have increased over the past decade, significant issues have developed regarding how data can be used for improving management. Big Data can be understood as large amounts of data generated by the Internet and a variety of connected smart devices and sensors. This book discusses the main challenges posed by Big Data in a manner relevant to both practitioners and scholars. It examines how companies can leverage Big Data analytics to act and optimize the business. This book brings together the theory and practice of management in the era of Big Data. It offers a look at the current state of Big Data, including a comprehensive overview of both research and practical applications. By bringing together conceptual thinking and empirical research on the nature, meaning, and development of Big Data in management, this book unifies research on Big Data in management to stimulate new directions for academic investigation as well as practice.
| Author | : Florin Pop |
| Publisher | : Springer |
| Total Pages | : 509 |
| Release | : 2016-10-27 |
| Genre | : Computers |
| ISBN | : 3319448811 |
Serving as a flagship driver towards advance research in the area of Big Data platforms and applications, this book provides a platform for the dissemination of advanced topics of theory, research efforts and analysis, and implementation oriented on methods, techniques and performance evaluation. In 23 chapters, several important formulations of the architecture design, optimization techniques, advanced analytics methods, biological, medical and social media applications are presented. These chapters discuss the research of members from the ICT COST Action IC1406 High-Performance Modelling and Simulation for Big Data Applications (cHiPSet). This volume is ideal as a reference for students, researchers and industry practitioners working in or interested in joining interdisciplinary works in the areas of intelligent decision systems using emergent distributed computing paradigms. It will also allow newcomers to grasp the key concerns and their potential solutions.
| Author | : Management Association, Information Resources |
| Publisher | : IGI Global |
| Total Pages | : 2523 |
| Release | : 2016-04-20 |
| Genre | : Computers |
| ISBN | : 1466698411 |
The digital age has presented an exponential growth in the amount of data available to individuals looking to draw conclusions based on given or collected information across industries. Challenges associated with the analysis, security, sharing, storage, and visualization of large and complex data sets continue to plague data scientists and analysts alike as traditional data processing applications struggle to adequately manage big data. Big Data: Concepts, Methodologies, Tools, and Applications is a multi-volume compendium of research-based perspectives and solutions within the realm of large-scale and complex data sets. Taking a multidisciplinary approach, this publication presents exhaustive coverage of crucial topics in the field of big data including diverse applications, storage solutions, analysis techniques, and methods for searching and transferring large data sets, in addition to security issues. Emphasizing essential research in the field of data science, this publication is an ideal reference source for data analysts, IT professionals, researchers, and academics.
| Author | : Juan Antonio Lossio-Ventura |
| Publisher | : Springer |
| Total Pages | : 158 |
| Release | : 2017-03-06 |
| Genre | : Computers |
| ISBN | : 3319552090 |
This book constitutes the refereed proceedings of the Second Annual International Symposium on Information Management and Big Data, SIMBig 2015, held in Cusco, Peru, in September 2015, and of the Third Annual International Symposium on Information Management and Big Data, SIMBig 2016, held in Cusco, Peru, in September 2016. The 11 revised full papers presented were carefully reviewed and selected from 70 submissions. The papers address issues such as Data Science, Big Data, Data Mining, Natural Language Processing, Bio NLP, Text Mining, Information Retrieval, Machine Learning, Semantic Web, Ontologies, Web Mining, Knowledge Representation and Linked Open Data, Social Networks, Social Web and Web Science, Information Visualization, OLAP, Data Warehousing, Business Intelligence, Spatiotemporal Data, Health Care, Agent-based Systems, Reasoning and Logic, Constraints, Satisfiability, and Search.
| Author | : Katherine O'Keefe |
| Publisher | : Kogan Page Publishers |
| Total Pages | : 345 |
| Release | : 2018-05-03 |
| Genre | : Business & Economics |
| ISBN | : 0749482052 |
Information and how we manage, process and govern it is becoming increasingly important as organizations ride the wave of the big data revolution. Ethical Data and Information Management offers a practical guide for people in organizations who are tasked with implementing information management projects. It sets out, in a clear and structured way, the fundamentals of ethics, and provides practical and pragmatic methods for organizations to embed ethical principles and practices into their management and governance of information. Written by global experts in the field, Ethical Data and Information Management is an important book addressing a topic high on the information management agenda. Key coverage includes how to build ethical checks and balances into data governance decision making; using quality management methods to assess and evaluate the ethical nature of processing during design; change methods to communicate ethical values; how to avoid common problems that affect ethical action; and how to make the business case for ethical behaviours.
| Author | : Rajendra Akerkar |
| Publisher | : CRC Press |
| Total Pages | : 566 |
| Release | : 2013-12-05 |
| Genre | : Business & Economics |
| ISBN | : 1466578378 |
Due to market forces and technological evolution, Big Data computing is developing at an increasing rate. A wide variety of novel approaches and tools have emerged to tackle the challenges of Big Data, creating both more opportunities and more challenges for students and professionals in the field of data computation and analysis. Presenting a mix of industry cases and theory, Big Data Computing discusses the technical and practical issues related to Big Data in intelligent information management. Emphasizing the adoption and diffusion of Big Data tools and technologies in industry, the book introduces a broad range of Big Data concepts, tools, and techniques. It covers a wide range of research, and provides comparisons between state-of-the-art approaches. Comprised of five sections, the book focuses on: What Big Data is and why it is important Semantic technologies Tools and methods Business and economic perspectives Big Data applications across industries
