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Author: William D. Mawby Publisher: Quality Press ISBN: 195105816X Category : Computers Languages : en Pages : 116
Book Description
More organizations and their leaders are looking to big data to transform processes and elevate the quality of products and services. Yet, gathering and storing large amounts of data isn't the quick fix often sought after. Without analysts-the human component-to interpret that data, the cost of incorrect or misinterpreted data can greatly impact organizations. In this book, William Mawby examines the claims of big data analysis in detail. Using examples to illustrate potential problems that may lead to inefficient and inaccurate results, Mawby helps practitioners avoid potential pitfalls and offers application methods to incorporate big data analytics into your company that will enhance your analytic efforts. William D. Mawby, Ph.D. has extensive consulting, teaching, and project experience and has taught more than 200 courses on many subjects in statistics and mathematics. He is currently writing, teaching courses on climate change and big data, and volunteering at the American Association for the Advancement of Science and the Union of Concerned Scientists.
Author: William D. Mawby Publisher: Quality Press ISBN: 195105816X Category : Computers Languages : en Pages : 116
Book Description
More organizations and their leaders are looking to big data to transform processes and elevate the quality of products and services. Yet, gathering and storing large amounts of data isn't the quick fix often sought after. Without analysts-the human component-to interpret that data, the cost of incorrect or misinterpreted data can greatly impact organizations. In this book, William Mawby examines the claims of big data analysis in detail. Using examples to illustrate potential problems that may lead to inefficient and inaccurate results, Mawby helps practitioners avoid potential pitfalls and offers application methods to incorporate big data analytics into your company that will enhance your analytic efforts. William D. Mawby, Ph.D. has extensive consulting, teaching, and project experience and has taught more than 200 courses on many subjects in statistics and mathematics. He is currently writing, teaching courses on climate change and big data, and volunteering at the American Association for the Advancement of Science and the Union of Concerned Scientists.
Author: Paul Zikopoulos Publisher: McGraw Hill Professional ISBN: 0071790543 Category : Computers Languages : en Pages : 176
Book Description
Big Data represents a new era in data exploration and utilization, and IBM is uniquely positioned to help clients navigate this transformation. This book reveals how IBM is leveraging open source Big Data technology, infused with IBM technologies, to deliver a robust, secure, highly available, enterprise-class Big Data platform. The three defining characteristics of Big Data--volume, variety, and velocity--are discussed. You'll get a primer on Hadoop and how IBM is hardening it for the enterprise, and learn when to leverage IBM InfoSphere BigInsights (Big Data at rest) and IBM InfoSphere Streams (Big Data in motion) technologies. Industry use cases are also included in this practical guide. Learn how IBM hardens Hadoop for enterprise-class scalability and reliability Gain insight into IBM's unique in-motion and at-rest Big Data analytics platform Learn tips and tricks for Big Data use cases and solutions Get a quick Hadoop primer
Author: Mohammed M. Alani Publisher: Springer ISBN: 3319764721 Category : Computers Languages : en Pages : 214
Book Description
This timely text/reference reviews the state of the art of big data analytics, with a particular focus on practical applications. An authoritative selection of leading international researchers present detailed analyses of existing trends for storing and analyzing big data, together with valuable insights into the challenges inherent in current approaches and systems. This is further supported by real-world examples drawn from a broad range of application areas, including healthcare, education, and disaster management. The text also covers, typically from an application-oriented perspective, advances in data science in such areas as big data collection, searching, analysis, and knowledge discovery. Topics and features: Discusses a model for data traffic aggregation in 5G cellular networks, and a novel scheme for resource allocation in 5G networks with network slicing Explores methods that use big data in the assessment of flood risks, and apply neural networks techniques to monitor the safety of nuclear power plants Describes a system which leverages big data analytics and the Internet of Things in the application of drones to aid victims in disaster scenarios Proposes a novel deep learning-based health data analytics application for sleep apnea detection, and a novel pathway for diagnostic models of headache disorders Reviews techniques for educational data mining and learning analytics, and introduces a scalable MapReduce graph partitioning approach for high degree vertices Presents a multivariate and dynamic data representation model for the visualization of healthcare data, and big data analytics methods for software reliability assessment This practically-focused volume is an invaluable resource for all researchers, academics, data scientists and business professionals involved in the planning, designing, and implementation of big data analytics projects. Dr. Mohammed M. Alani is an Associate Professor in Computer Engineering and currently is the Provost at Al Khawarizmi International College, Abu Dhabi, UAE. Dr. Hissam Tawfik is a Professor of Computer Science in the School of Computing, Creative Technologies & Engineering at Leeds Beckett University, UK. Dr. Mohammed Saeed is a Professor in Computing and currently is the Vice President for Academic Affairs and Research at the University of Modern Sciences, Dubai, UAE. Dr. Obinna Anya is a Research Staff Member at IBM Research – Almaden, San Jose, CA, USA.
Author: Kim H. Pries Publisher: CRC Press ISBN: 1482234521 Category : Computers Languages : en Pages : 576
Book Description
With this book, managers and decision makers are given the tools to make more informed decisions about big data purchasing initiatives. Big Data Analytics: A Practical Guide for Managers not only supplies descriptions of common tools, but also surveys the various products and vendors that supply the big data market.Comparing and contrasting the dif
Author: Soraya Sedkaoui Publisher: John Wiley & Sons ISBN: 1119528054 Category : Computers Languages : en Pages : 224
Book Description
The main purpose of this book is to investigate, explore and describe approaches and methods to facilitate data understanding through analytics solutions based on its principles, concepts and applications. But analyzing data is also about involving the use of software. For this, and in order to cover some aspect of data analytics, this book uses software (Excel, SPSS, Python, etc) which can help readers to better understand the analytics process in simple terms and supporting useful methods in its application.
Author: Pushpa Singh Publisher: Springer ISBN: 9789819704477 Category : Mathematics Languages : en Pages : 0
Book Description
This book presents an in-depth analysis of successful data-driven initiatives, highlighting how organizations have leveraged data to drive decision-making processes, optimize operations, and achieve remarkable outcomes. Through case studies, readers gain valuable insights and learn practical strategies for implementing data analytics, big data, and machine learning solutions in their own organizations. The book discusses the transformative power of data analytics and big data in various industries and sectors and how machine learning applications have revolutionized exploration by enabling advanced data analysis techniques for mapping, geospatial analysis, and environmental monitoring, enhancing our understanding of the world and its dynamic processes. This book explores how big data explosion, the power of analytics and machine learning revolution can bring new prospects and opportunities in the dynamic and data-rich landscape. It highlights the future research directions in data analytics, big data, and machine learning that explores the emerging trends, challenges, and opportunities in these fields by covering interdisciplinary approaches such as handling and analyzing real-time and streaming data.
Author: Arun K. Somani Publisher: CRC Press ISBN: 1351180320 Category : Computers Languages : en Pages : 399
Book Description
The proposed book will discuss various aspects of big data Analytics. It will deliberate upon the tools, technology, applications, use cases and research directions in the field. Chapters would be contributed by researchers, scientist and practitioners from various reputed universities and organizations for the benefit of readers.
Author: William D. Mawby
Author: William D. Mawby
Author: Paul Zikopoulos
Author: William D. Mawby
Author: Pushpa Singh
Author: Mohammed M. Alani
Author: Kim H. Pries
Author: Soraya Sedkaoui
Author: Karen L. Webber
Author: Pushpa Singh
Author: Arun K. Somani