Big Data Factories
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Big Data Factories
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Author : Sorin Adam Matei
language : en
Publisher: Springer
Release Date : 2017-11-27
Big Data Factories written by Sorin Adam Matei and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-27 with Computers categories.
The book proposes a systematic approach to big data collection, documentation and development of analytic procedures that foster collaboration on a large scale. This approach, designated as “data factoring” emphasizes the need to think of each individual dataset developed by an individual project as part of a broader data ecosystem, easily accessible and exploitable by parties not directly involved with data collection and documentation. Furthermore, data factoring uses and encourages pre-analytic operations that add value to big data sets, especially recombining and repurposing. The book proposes a research-development agenda that can undergird an ideal data factory approach. Several programmatic chapters discuss specialized issues involved in data factoring (documentation, meta-data specification, building flexible, yet comprehensive data ontologies, usability issues involved in collaborative tools, etc.). The book also presents case studies for data factoring and processing that can lead to building better scientific collaboration and data sharing strategies and tools. Finally, the book presents the teaching utility of data factoring and the ethical and privacy concerns related to it. Chapter 9 of this book is available open access under a CC BY 4.0 license at link.springer.com
Big Data Applications In Industry 4 0
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Author : P. Kaliraj
language : en
Publisher: CRC Press
Release Date : 2022-02-09
Big Data Applications In Industry 4 0 written by P. Kaliraj and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-09 with Business & Economics categories.
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
Information Systems For The Fashion And Apparel Industry
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Author : Tsan-Ming Jason Choi
language : en
Publisher: Woodhead Publishing
Release Date : 2016-04-13
Information Systems For The Fashion And Apparel Industry written by Tsan-Ming Jason Choi and has been published by Woodhead Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-13 with Computers categories.
Information Systems for the Fashion and Apparel Industry brings together trends and developments in fashion information systems, industrial case-studies, and insights from an international team of authors. The fashion and apparel industry is fast-growing and highly influential. Computerized information systems are essential to support fashion business operations and recent developments in social media, mobile commerce models, radio frequency identification (RFID) technologies, and ERP systems are all driving innovative business measures in the industry. After an introductory chapter outlining key decision points and information requirements in fast fashion supply chains, Part One focuses on the principles of fashion information systems, with chapters covering how decision making in the apparel supply chains can be improved through the use of fuzzy logic, RFID technologies, evolutionary optimization techniques, and artificial neural networks. Part Two then reviews the range of applications for information systems in the fashion and apparel industry to improve customer choice, aid design, implement intelligent forecasting and procurement systems, and manage inventory and returns. - Provides systematic and comprehensive coverage of information systems for the fashion and apparel industry - Combines recent developments and industrial best-practices in apparel supply chain management in order to meet the needs of the fashion and apparel industry professionals and academics - Features input from a team of highly knowledgeable authors with a range of professional and academic experience, overseen by an editor who is a leading expert in the field - Reviews the range of applications for information systems in the fashion and apparel industry to improve customer choice, aid design, implement intelligent forecasting and procurement systems, and manage inventory and returns
Data Warehousing In The Age Of Big Data
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Author : Krish Krishnan
language : en
Publisher: Newnes
Release Date : 2013-05-02
Data Warehousing In The Age Of Big Data written by Krish Krishnan and has been published by Newnes this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-05-02 with Computers categories.
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
Intelligent Manufacturing Systems
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Author : Andrew Kusiak
language : en
Publisher: Prentice Hall
Release Date : 1990
Intelligent Manufacturing Systems written by Andrew Kusiak and has been published by Prentice Hall this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990 with Computer integrated manufacturing systems categories.
Defining structure and functions of knowledge-based systems, this book presents hardware and software components of flexible machining, flexible assembly and computer-integrated manufacturing systems. Discussed are such areas as process planning, group technology and lay-out design.
Artificial Intelligence For Big Data
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Author : Anand Deshpande
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-05-22
Artificial Intelligence For Big Data written by Anand Deshpande and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-22 with Computers categories.
Build next-generation Artificial Intelligence systems with Java Key Features Implement AI techniques to build smart applications using Deeplearning4j Perform big data analytics to derive quality insights using Spark MLlib Create self-learning systems using neural networks, NLP, and reinforcement learning Book Description In this age of big data, companies have larger amount of consumer data than ever before, far more than what the current technologies can ever hope to keep up with. However, Artificial Intelligence closes the gap by moving past human limitations in order to analyze data. With the help of Artificial Intelligence for big data, you will learn to use Machine Learning algorithms such as k-means, SVM, RBF, and regression to perform advanced data analysis. You will understand the current status of Machine and Deep Learning techniques to work on Genetic and Neuro-Fuzzy algorithms. In addition, you will explore how to develop Artificial Intelligence algorithms to learn from data, why they are necessary, and how they can help solve real-world problems. By the end of this book, you'll have learned how to implement various Artificial Intelligence algorithms for your big data systems and integrate them into your product offerings such as reinforcement learning, natural language processing, image recognition, genetic algorithms, and fuzzy logic systems. What you will learn Manage Artificial Intelligence techniques for big data with Java Build smart systems to analyze data for enhanced customer experience Learn to use Artificial Intelligence frameworks for big data Understand complex problems with algorithms and Neuro-Fuzzy systems Design stratagems to leverage data using Machine Learning process Apply Deep Learning techniques to prepare data for modeling Construct models that learn from data using open source tools Analyze big data problems using scalable Machine Learning algorithms Who this book is for This book is for you if you are a data scientist, big data professional, or novice who has basic knowledge of big data and wish to get proficiency in Artificial Intelligence techniques for big data. Some competence in mathematics is an added advantage in the field of elementary linear algebra and calculus.
Guide To Industrial Analytics
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Author : Richard Hill
language : en
Publisher: Springer Nature
Release Date : 2021-09-27
Guide To Industrial Analytics written by Richard Hill and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-27 with Computers categories.
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.
Big Data
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Author : Bill Schmarzo
language : en
Publisher: John Wiley & Sons
Release Date : 2013-10-07
Big Data written by Bill Schmarzo and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-10-07 with Business & Economics categories.
Leverage big data to add value to your business Social media analytics, web-tracking, and other technologies help companies acquire and handle massive amounts of data to better understand their customers, products, competition, and markets. Armed with the insights from big data, companies can improve customer experience and products, add value, and increase return on investment. The tricky part for busy IT professionals and executives is how to get this done, and that's where this practical book comes in. Big Data: Understanding How Data Powers Big Business is a complete how-to guide to leveraging big data to drive business value. Full of practical techniques, real-world examples, and hands-on exercises, this book explores the technologies involved, as well as how to find areas of the organization that can take full advantage of big data. Shows how to decompose current business strategies in order to link big data initiatives to the organization’s value creation processes Explores different value creation processes and models Explains issues surrounding operationalizing big data, including organizational structures, education challenges, and new big data-related roles Provides methodology worksheets and exercises so readers can apply techniques Includes real-world examples from a variety of organizations leveraging big data Big Data: Understanding How Data Powers Big Business is written by one of Big Data's preeminent experts, William Schmarzo. Don't miss his invaluable insights and advice.
Keeping Up With The Quants
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Author : Thomas H. Davenport
language : en
Publisher: Harvard Business Press
Release Date : 2013-05-21
Keeping Up With The Quants written by Thomas H. Davenport and has been published by Harvard Business Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-05-21 with Business & Economics categories.
Why Everyone Needs Analytical Skills Welcome to the age of data. No matter your interests (sports, movies, politics), your industry (finance, marketing, technology, manufacturing), or the type of organization you work for (big company, nonprofit, small start-up)—your world is awash with data. As a successful manager today, you must be able to make sense of all this information. You need to be conversant with analytical terminology and methods and able to work with quantitative information. This book promises to become your “quantitative literacy" guide—helping you develop the analytical skills you need right now in order to summarize data, find the meaning in it, and extract its value. In Keeping Up with the Quants, authors, professors, and analytics experts Thomas Davenport and Jinho Kim offer practical tools to improve your understanding of data analytics and enhance your thinking and decision making. You’ll gain crucial skills, including: How to formulate a hypothesis How to gather and analyze relevant data How to interpret and communicate analytical results How to develop habits of quantitative thinking How to deal effectively with the “quants” in your organization Big data and the analytics based on it promise to change virtually every industry and business function over the next decade. If you don’t have a business degree or if you aren’t comfortable with statistics and quantitative methods, this book is for you. Keeping Up with the Quants will give you the skills you need to master this new challenge—and gain a significant competitive edge.
The Dark Factory And The Future Of Manufacturing
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Author : Philip J. Gisi
language : en
Publisher: CRC Press
Release Date : 2024-02-23
The Dark Factory And The Future Of Manufacturing written by Philip J. Gisi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-23 with Business & Economics categories.
The world of manufacturing is undergoing significant changes driven by various factors and technological advancements. Automation and robotics technologies are revolutionizing manufacturing processes. Robotic systems are being increasingly used for repetitive and precise tasks, improving efficiency, quality, and safety. The Internet of Things (IoT) is enabling connectivity and data exchange between devices and systems. Manufacturing generates vast amounts of data and is leveraging this data through advanced analytics, providing valuable insights to optimize production processes, predict maintenance needs, and improve supply chain management. Additive Manufacturing has also gained significant traction in manufacturing. It enables the creation of complex parts and prototypes, customization, and rapid prototyping. Supply chains are becoming more interconnected and digitally integrated. Technologies such as blockchain enable transparent and secure transactions, traceability, and efficient inventory management. These trends and others are reshaping the manufacturing industry, promoting increased efficiency, agility, and sustainability. Manufacturers must be aware, understand, and embrace these changes to stay competitive and meet the evolving demands of customers in the modern era. This book enhances the awareness and understanding of these core technologies by explaining what they are and how they are being used in manufacturing. In addition, it provides practical suggestions on how to advance manufacturing in light of these changes. The book provides a view into the future and direction on how to navigate the journey to a more automated, smarter, and continuously learning factory. This book consolidates the major elements of the fourth industrial revolution and describes them in clear terms within the context of integrated manufacturing. It creates awareness and a fundamental understanding of the advanced technologies that are coming together to facilitate highly automated, smarter, agile, and sustainable operations.