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Author: Gerardus Blokdyk
Publisher:
ISBN: 9780655123262
Category :
Languages : en
Pages : 0
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Book Description
Author: Gerardus Blokdyk
Publisher:
ISBN: 9780655123262
Category :
Languages : en
Pages : 0
Get Book Here
Book Description
Author: Gerardus Blokdyk
Publisher: 5starcooks
ISBN: 9780655173267
Category :
Languages : en
Pages : 124
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Book Description
How to Secure Industrial big data? How do we make it meaningful in connecting Industrial big data with what users do day-to-day? Why is it important to have senior management support for a Industrial big data project? How likely is the current Industrial big data plan to come in on schedule or on budget? What are the Key enablers to make this Industrial big data move? This exclusive Industrial big data self-assessment will make you the established Industrial big data domain auditor by revealing just what you need to know to be fluent and ready for any Industrial big data challenge. How do I reduce the effort in the Industrial big data work to be done to get problems solved? How can I ensure that plans of action include every Industrial big data task and that every Industrial big data outcome is in place? How will I save time investigating strategic and tactical options and ensuring Industrial big data costs are low? How can I deliver tailored Industrial big data advice instantly with structured going-forward plans? There's no better guide through these mind-expanding questions than acclaimed best-selling author Gerard Blokdyk. Blokdyk ensures all Industrial big data essentials are covered, from every angle: the Industrial big data self-assessment shows succinctly and clearly that what needs to be clarified to organize the required activities and processes so that Industrial big data outcomes are achieved. Contains extensive criteria grounded in past and current successful projects and activities by experienced Industrial big data practitioners. Their mastery, combined with the easy elegance of the self-assessment, provides its superior value to you in knowing how to ensure the outcome of any efforts in Industrial big data are maximized with professional results. Your purchase includes access details to the Industrial big data self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows you exactly what to do next. Your exclusive instant access details can be found in your book.
Author: Keshav Kaushik
Publisher: CRC Press
ISBN: 1000936880
Category : Computers
Languages : en
Pages : 247
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Book Description
This book aims to provide readers with a comprehensive guide to the fundamentals of big data analytics and its applications in various industries and smart societies. What sets this book apart is its in-depth coverage of different aspects of big data analytics, including machine learning algorithms, spatial data analytics, and IoT-based smart systems for precision agriculture. The book also delves into the use of big data analytics in healthcare, energy management, and agricultural development, among others. The authors have used clear and concise language, along with relevant examples and case studies, to help readers understand the complex concepts involved in big data analytics. Key Features: Comprehensive coverage of the fundamentals of big data analytics In-depth discussion of different aspects of big data analytics, including machine learning algorithms, spatial data analytics, and IoT-based smart systems. Practical examples and case studies to help readers understand complex concepts. Coverage of the use of big data analytics in various industries, including healthcare, energy management, and agriculture Discussion of challenges and legal frameworks involved in big data analytics. Clear and concise language that is easy to understand. This book is a valuable resource for business owners, data analysts, students, and anyone interested in the field of big data analytics. It provides readers with the tools they need to leverage the power of big data and make informed decisions that can help their organizations succeed. Whether you are new to the field or an experienced practitioner, "Demystifying Big Data Analytics for Industries and Smart Societies" is must-read.
Author: Thomas Davenport
Publisher: Harvard Business Review Press
ISBN: 1422168174
Category : Business & Economics
Languages : en
Pages : 241
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Book Description
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: José María Cavanillas
Publisher: Springer
ISBN: 3319215698
Category : Computers
Languages : en
Pages : 312
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Book Description
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.
Author: P. Kaliraj
Publisher: CRC Press
ISBN: 1000537668
Category : Computers
Languages : en
Pages : 446
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Book Description
Industry 4.0 is the latest technological innovation in manufacturing with the goal to increase productivity in a flexible and efficient manner. Changing the way in which manufacturers operate, this revolutionary transformation is powered by various technology advances including Big Data analytics, Internet of Things (IoT), Artificial Intelligence (AI), and cloud computing. Big Data analytics has been identified as one of the significant components of Industry 4.0, as it provides valuable insights for smart factory management. Big Data and Industry 4.0 have the potential to reduce resource consumption and optimize processes, thereby playing a key role in achieving sustainable development. Big Data Applications in Industry 4.0 covers the recent advancements that have emerged in the field of Big Data and its applications. The book introduces the concepts and advanced tools and technologies for representing and processing Big Data. It also covers applications of Big Data in such domains as financial services, education, healthcare, biomedical research, logistics, and warehouse management. Researchers, students, scientists, engineers, and statisticians can turn to this book to learn about concepts, technologies, and applications that solve real-world problems. Features An introduction to data science and the types of data analytics methods accessible today An overview of data integration concepts, methodologies, and solutions A general framework of forecasting principles and applications, as well as basic forecasting models including naïve, moving average, and exponential smoothing models A detailed roadmap of the Big Data evolution and its related technological transformation in computing, along with a brief description of related terminologies The application of Industry 4.0 and Big Data in the field of education The features, prospects, and significant role of Big Data in the banking industry, as well as various use cases of Big Data in banking, finance services, and insurance Implementing a Data Lake (DL) in the cloud and the significance of a data lake in decision making
Author: P Suresh
Publisher: CRC Press
ISBN: 1000815749
Category : Computers
Languages : en
Pages : 205
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Book Description
The significant objective of this edited book is to bridge the gap between smart manufacturing and big data by exploring the challenges and limitations. Companies employ big data technology in the manufacturing field to acquire data about the products. Manufacturing companies could gain a deep business insight by tracking customer details, monitoring fuel consumption, detecting product defects, and supply chain management. Moreover, the convergence of smart manufacturing and big data analytics currently suffers due to data privacy concern, short of qualified personnel, inadequate investment, long-term storage management of high-quality data. The technological advancement makes the data storage more accessible, cheaper and the convergence of these technologies seems to be more promising in the recent era. This book identified the innovative challenges in the industrial domains by integrating heterogeneous data sources such as structured data, semi-structures data, geo-spatial data, textual information, multimedia data, social networking data, etc. It promotes data-driven business modelling processes by adopting big data technologies in the manufacturing industry. Big data analytics is emerging as a promising discipline in the manufacturing industry to build the rigid industrial data platforms. Moreover, big data facilitates process automation in the complete lifecycle of product design and tracking. This book is an essential guide and reference since it synthesizes interdisciplinary theoretical concepts, definitions, and models, involved in smart manufacturing domain. It also provides real-world scenarios and applications, making it accessible to a wider interdisciplinary audience. Features The readers will get an overview about the smart manufacturing system which enables optimized manufacturing processes and benefits the users by increasing overall profit The researchers will get insight about how the big data technology leverages in finding new associations, factors and patterns through data stream observations in real time smart manufacturing systems The industrialist can get an overview about the detection of defects in design, rapid response to market, innovative products to meet the customer requirement which can benefit their per capita income in better way Discusses technical viewpoints, concepts, theories, and underlying assumptions that are used in smart manufacturing Information delivered in a user-friendly manner for students, researchers, industrial experts, and business innovators, as well as for professionals and practitioners
Author: Richard Hill
Publisher: Springer Nature
ISBN: 3030791041
Category : Computers
Languages : en
Pages : 285
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Book Description
This textbook describes the hands-on application of data science techniques to solve problems in manufacturing and the Industrial Internet of Things (IIoT). Monitoring and managing operational performance is a crucial activity for industrial and business organisations. The emergence of low-cost, accessible computing and storage, through Industrial Digital Technologies (IDT) and Industry 4.0, has generated considerable interest in innovative approaches to doing more with data. Data science, predictive analytics, machine learning, artificial intelligence and general approaches to modelling, simulating and visualising industrial systems have often been considered topics only for research labs and academic departments. This textbook debunks the mystique around applied data science and shows readers, using tutorial-style explanations and real-life case studies, how practitioners can develop their own understanding of performance to achieve tangible business improvements. All exercises can be completed with commonly available tools, many of which are free to install and use. Readers will learn how to use tools to investigate, diagnose, propose and implement analytics solutions that will provide explainable results to deliver digital transformation.
Author: Gerardus Blokdyk
Publisher: 5starcooks
ISBN: 9780655447276
Category :
Languages : en
Pages : 278
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Book Description
Is the measure of success for Big Data Storage understandable to a variety of people? Which individuals, teams or departments will be involved in Big Data Storage? How will the Big Data Storage team and the organization measure complete success of Big Data Storage? How do senior leaders actions reflect a commitment to the organizations Big Data Storage values? Is there a recommended audit plan for routine surveillance inspections of Big Data Storage's gains? This premium Big Data Storage self-assessment will make you the established Big Data Storage domain auditor by revealing just what you need to know to be fluent and ready for any Big Data Storage challenge. How do I reduce the effort in the Big Data Storage work to be done to get problems solved? How can I ensure that plans of action include every Big Data Storage task and that every Big Data Storage outcome is in place? How will I save time investigating strategic and tactical options and ensuring Big Data Storage costs are low? How can I deliver tailored Big Data Storage advice instantly with structured going-forward plans? There's no better guide through these mind-expanding questions than acclaimed best-selling author Gerard Blokdyk. Blokdyk ensures all Big Data Storage essentials are covered, from every angle: the Big Data Storage self-assessment shows succinctly and clearly that what needs to be clarified to organize the required activities and processes so that Big Data Storage outcomes are achieved. Contains extensive criteria grounded in past and current successful projects and activities by experienced Big Data Storage practitioners. Their mastery, combined with the easy elegance of the self-assessment, provides its superior value to you in knowing how to ensure the outcome of any efforts in Big Data Storage are maximized with professional results. Your purchase includes access details to the Big Data Storage self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows you exactly what to do next. Your exclusive instant access details can be found in your book. You will receive the following contents with New and Updated specific criteria: - The latest quick edition of the book in PDF - The latest complete edition of the book in PDF, which criteria correspond to the criteria in... - The Self-Assessment Excel Dashboard, and... - Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation ...plus an extra, special, resource that helps you with project managing. INCLUDES LIFETIME SELF ASSESSMENT UPDATES Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.
Author: Krish Krishnan
Publisher: Newnes
ISBN: 0124059201
Category : Computers
Languages : en
Pages : 371
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Book Description
Data Warehousing in the Age of the Big Data will help you and your organization make the most of unstructured data with your existing data warehouse. As Big Data continues to revolutionize how we use data, it doesn't have to create more confusion. Expert author Krish Krishnan helps you make sense of how Big Data fits into the world of data warehousing in clear and concise detail. The book is presented in three distinct parts. Part 1 discusses Big Data, its technologies and use cases from early adopters. Part 2 addresses data warehousing, its shortcomings, and new architecture options, workloads, and integration techniques for Big Data and the data warehouse. Part 3 deals with data governance, data visualization, information life-cycle management, data scientists, and implementing a Big Data–ready data warehouse. Extensive appendixes include case studies from vendor implementations and a special segment on how we can build a healthcare information factory. Ultimately, this book will help you navigate through the complex layers of Big Data and data warehousing while providing you information on how to effectively think about using all these technologies and the architectures to design the next-generation data warehouse. - Learn how to leverage Big Data by effectively integrating it into your data warehouse. - Includes real-world examples and use cases that clearly demonstrate Hadoop, NoSQL, HBASE, Hive, and other Big Data technologies - Understand how to optimize and tune your current data warehouse infrastructure and integrate newer infrastructure matching data processing workloads and requirements
