New Approaches to Data Analytics and Internet of Things Through Digital Twin, P. Karthikeyan, Polinpapilinho F Katina, S.P. Anandaraj
Автор: P. Karthikeyan, Polinpapilinho F Katina, S.P. Anandaraj Название: New Approaches to Data Analytics and Internet of Things Through Digital Twin ISBN: 1668457229 ISBN-13(EAN): 9781668457221 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 42134.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Considers how data analytics and the internet of things can be used successfully within the field of digital twin as well as the potential future directions of these technologies. The book covers key topics such as edge networks, deep learning, intelligent data analytics, and knowledge discovery.
Автор: Obaid Ahmed J., Polkowski Zdzislaw, Bhushan Bharat Название: Advanced Practical Approaches to Web Mining Techniques and Application ISBN: 1799894274 ISBN-13(EAN): 9781799894278 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 30908.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Illustrates all the concepts of web mining and fosters transformative, multidisciplinary, and novel approaches that introduce the practical method of analysing various web data sources and extracting knowledge by taking into consideration the unique challenges present in the environment.
Описание: The availability of big data, low-cost commodity hardware, and new information management and analytic software have produced a unique moment in the history of data analysis. The convergence of these trends means that we have the capabilities required to analyze astonishing data sets quickly and cost-effectively for the first time in history. They represent a genuine leap forward and a clear opportunity to realize enormous gains in terms of efficiency, productivity, revenue, and profitability especially in digital marketing. Data plays a huge role in understanding valuable insights about target demographics and customer preferences. From every interaction with technology, regardless of whether it is active or passive, we are creating new data that can describe us. If analyzed correctly, these data points can explain a lot about our behavior, personalities, and life events. Companies can leverage these insights for product improvements, business strategy, and marketing campaigns to cater to the target customers.
Big Data Analytics for Improved Accuracy, Efficiency, and Decision Making in Digital Marketing aids understanding of big data in terms of digital marketing for meaningful analysis of information that can improve marketing efforts and strategies using the latest digital techniques. The chapters cover a wide array of essential marketing topics and techniques, including search engine marketing, consumer behavior, social media marketing, online advertising, and how they interact with big data. This book is essential for professionals and researchers working in the field of analytics, data, and digital marketing, along with marketers, advertisers, brand managers, social media specialists, managers, sales professionals, practitioners, researchers, academicians, and students looking for the latest information on how big data is being used in digital marketing strategies.
Автор: Geng Название: Internet of Things and Data Analytics Handbook ISBN: 1119173647 ISBN-13(EAN): 9781119173649 Издательство: Wiley Рейтинг: Цена: 20742.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book examines the Internet of Things (IoT) and Data Analytics from a technical, application, and business point of view.
Автор: Chishti Mohammad Ahsan, Saleem Tausifa Jan Название: Big Data Analytics for Internet of Things ISBN: 1119740754 ISBN-13(EAN): 9781119740759 Издательство: Wiley Рейтинг: Цена: 17258.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: BIG DATA ANALYTICS FOR INTERNET OF THINGS
Discover the latest developments in IoT Big Data with a new resource from established and emerging leaders in the field
Big Data Analytics for Internet of Things delivers a comprehensive overview of all aspects of big data analytics in Internet of Things (IoT) systems. The book includes discussions of the enabling technologies of IoT data analytics, types of IoT data analytics, challenges in IoT data analytics, demand for IoT data analytics, computing platforms, analytical tools, privacy, and security.
The distinguished editors have included resources that address key techniques in the analysis of IoT data. The book demonstrates how to select the appropriate techniques to unearth valuable insights from IoT data and offers novel designs for IoT systems.
With an abiding focus on practical strategies with concrete applications for data analysts and IoT professionals, Big Data Analytics for Internet of Things also offers readers:
A thorough introduction to the Internet of Things, including IoT architectures, enabling technologies, and applications
An exploration of the intersection between the Internet of Things and Big Data, including IoT as a source of Big Data, the unique characteristics of IoT data, etc.
A discussion of the IoT data analytics, including the data analytical requirements of IoT data and the types of IoT analytics, including predictive, descriptive, and prescriptive analytics
A treatment of machine learning techniques for IoT data analytics
Perfect for professionals, industry practitioners, and researchers engaged in big data analytics related to IoT systems, Big Data Analytics for Internet of Things will also earn a place in the libraries of IoT designers and manufacturers interested in facilitating the efficient implementation of data analytics strategies.
1.Introduction to Industrial Analytics.- 2. Measuring Performance.- 3. Modelling and Simulating Systems.- 4. Optimising Systems.- 5. Production Control and Scheduling.- 6. Simulating Demand Forecasts.- 7. Investigating Time Series Data.- 8. Determining the Minimum Information for Effective Control.- 9. Constructing Machine Learning Models for Prediction.- 10. Exploring Model Accuracy.- 11. Building a Business Case for Sensing Technology Adoption.- 12. Improving Throughput by Utilising Sensor Data.- 13. Constructing a Digital Factory Model to Optimise Production.- 14. Examining a Digital Supply Chain.- 15. Probability Essentials.- 16. Building Simulations with Spreadsheets.- 17. Using Python to Construct Manufacturing Models.- 18. Predictive Analytics with KNIME.- 19. Using R to Evaluate Data.- 20. Example Case Study Data.
Автор: Minteer Andrew Название: Analytics for the Internet of Things (Iot) ISBN: 1787120732 ISBN-13(EAN): 9781787120730 Издательство: Неизвестно Цена: 9010.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Anandakumar Haldorai, Arulmurugan Ramu Название: Cognitive Social Mining Applications in Data Analytics and Forensics ISBN: 1522575227 ISBN-13(EAN): 9781522575221 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 28413.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Recently, there has been a rapid increase in interest regarding social network analysis in the data mining community. Cognitive radios are expected to play a major role in meeting this exploding traffic demand on social networks due to their ability to sense the environment, analyze outdoor parameters, and then make decisions for dynamic time, frequency, space, resource allocation, and management to improve the utilization of mining the social data.Cognitive Social Mining Applications in Data Analytics and Forensics is an essential reference source that reviews cognitive radio concepts and examines their applications to social mining using a machine learning approach so that an adaptive and intelligent mining is achieved. Featuring research on topics such as data mining, real-time ubiquitous social mining services, and cognitive computing, this book is ideally designed for social network analysts, researchers, academicians, and industry professionals.
Build a continuously learning and adapting organization that can extract increasing levels of business, customer and operational value from the amalgamation of data and advanced analytics such as AI and Machine Learning
Key features
Master the Big Data Business Model Maturity Index methodology to transition to a value-driven organizational mindset
Acquire implementable knowledge on digital transformation through 8 practical laws
Explore the economics behind digital assets (data and analytics) that appreciate in value when constructed and deployed correctly
Book Description
In today's digital era, every organization has data, but just possessing enormous amounts of data is not a sufficient market discriminator. The Economics of Data, Analytics, and Digital Transformation aims to provide actionable insights into the real market discriminators, including an organization's data-fueled analytics products that inspire innovation, deliver insights, help make practical decisions, generate value, and produce mission success for the enterprise.
The book begins by first building your mindset to be value-driven and introducing the Big Data Business Model Maturity Index, its maturity index phases, and how to navigate the index. You will explore value engineering, where you will learn how to identify key business initiatives, stakeholders, advanced analytics, data sources, and instrumentation strategies that are essential to data science success. The book will help you accelerate and optimize your company's operations through AI and machine learning.
By the end of the book, you will have the tools and techniques to drive your organization's digital transformation.
Here are a few words from Dr. Kirk Borne, Data Scientist and Executive Advisor at Booz Allen Hamilton, about the book:
"Data analytics should first and foremost be about action and value. Consequently, the great value of this book is that it seeks to be actionable. It offers a dynamic progression of purpose-driven ignition points that you can act upon."
What you will learn
Train your organization to transition from being data-driven to being value-driven
Navigate and master the big data business model maturity index
Learn a methodology for determining the economic value of your data and analytics
Understand how AI and machine learning can create analytics assets that appreciate in value the more that they are used
Become aware of digital transformation misconceptions and pitfalls
Create empowered and dynamic teams that fuel your organization's digital transformation
Who this book is for
This book is designed to benefit everyone from students who aspire to study the economic fundamentals behind data and digital transformation to established business leaders and professionals who want to learn how to leverage data and analytics to accelerate their business careers.
Описание: Deliver enterprise data analytics success by following Prashanths prescriptive and practical techniques. Today, organizations across the globe are looking at ways to glean insights from data analytics and make good business decisions. However, not many business enterprises are successful in data analytics. According to Gartner, 80% of analytics programs do not deliver business outcomes. Mckinsey consulting says, less than 20% of the companies have achieved analytics at scale. So, how can a business enterprise avoid analytics failure and deliver business results? This book provides ten key analytics best practices that will improve the odds of delivering enterprise data analytics solutions successfully. It is intended for anyone who has a stake and interest in deriving insights from data analytics. The three key differentiating aspects of this book are: Practicality. This book offers prescriptive, superior, and practical guidance. Completeness. This book looks at data analytics holistically across the four key data analytics domains - data management, data engineering, data science, and data visualization. Neutrality. This book is technologically agnostic and looks at analytics concepts without any reference to commercial analytics products and technologies.
Описание: This book offers an introduction and hands-on examples that demonstrate how Learning Analytics (LA) can be used to enhance digital learning, teaching and training at various levels.
Автор: Digital Colibri, Lai Rudy, Potaczek Bartlomiej Название: Hands-On Big Data Analytics with PySpark ISBN: 183864413X ISBN-13(EAN): 9781838644130 Издательство: Неизвестно Рейтинг: Цена: 4780.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In this book, you`ll learn to implement some practical and proven techniques to improve aspects of programming and administration in Apache Spark. Techniques are demonstrated using practical examples and best practices. You will also learn how to use Spark and its Python API to create performant analytics with large-scale data.
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