Understanding data analytics and predictive modelling in the oil and gas industry, Kingshuk Srivastava, Thipendra P Singh, Manas Ranjan Pradhan, Vinit Kumar Gunjan
Описание: In this book, Dr. Soofastaei and his colleagues reveal how all mining managers can effectively deploy advanced analytics in their day-to-day operations- one business decision at a time. Most mining companies have a massive amount of data at their disposal. However, they cannot use the stored data in any meaningful way. The powerful new business tool-advanced analytics enables many mining companies to aggressively leverage their data in key business decisions and processes with impressive results. From statistical analysis to machine learning and artificial intelligence, the authors show how many analytical tools can improve decisions about everything in the mine value chain, from exploration to marketing. Combining the science of advanced analytics with the mining industrial business solutions, introduce the “Advanced Analytics in Mining Engineering Book” as a practical road map and tools for unleashing the potential buried in your company’s data. The book is aimed at providing mining executives, managers, and research and development teams with an understanding of the business value and applicability of different analytic approaches and helping data analytics leads by giving them a business framework in which to assess the value, cost, and risk of potential analytical solutions. In addition, the book will provide the next generation of miners – undergraduate and graduate IT and mining engineering students – with an understanding of data analytics applied to the mining industry. By providing a book with chapters structured in line with the mining value chain, we will provide a clear, enterprise-level view of where and how advanced data analytics can best be applied. This book highlights the potential to interconnect activities in the mining enterprise better. Furthermore, the book explores the opportunities for optimization and increased productivity offered by better interoperability along the mining value chain – in line with the emerging vision of creating a digital mine with much-enhanced capabilities for modeling, simulation, and the use of digital twins – in line with leading “digital” industries.
Автор: Thakkar Название: Predictive Analytics in Cloud, Fog, and Edge Computing ISBN: 303118033X ISBN-13(EAN): 9783031180330 Издательство: Springer Рейтинг: Цена: 23757.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book covers the relationship of recent technologies (such as Blockchain, IoT, and 5G) with the cloud computing as well as fog computing, and mobile edge computing. The relationship will not be limited to only architecture proposal, trends, and technical advancements. However, the book also explores the possibility of predictive analytics in cloud computing with respect to Blockchain, IoT, and 5G. The recent advancements in the internet-supported distributed computing i.e. cloud computing, has made it possible to process the bulk amount of data in a parallel and distributed. This has made it a lucrative technology to process the data generated from technologies such as Blockchain, IoT, and 5G. However, there are several issues a Cloud Service Provider (CSP) encounters, such as Blockchain security in cloud, IoT elasticity and scalability management in cloud, Service Level Agreement (SLA) compliances for 5G, Resource management, Load balancing, and Fault-tolerance. This edited book will discuss the aforementioned issues in connection with Blockchain, IoT, and 5G. Moreover, the book discusses how the cloud computing is not sufficient and one needs to use fog computing, and edge computing to efficiently process the data generated from IoT, and 5G. Moreover, the book shows how smart city, smart healthcare system, and smart communities are few of the most relevant IoT applications where fog computing plays a significant role. The book discusses the limitation of fog computing and the need for the edge computing to further reduce the network latency to process streaming data from IoT devices. The book also explores power of predictive analytics of Blockchain, IoT, and 5G data in cloud computing with its sister technologies. Since, the amount of resources increases day-by day, artificial intelligence (AI) tools are becoming more popular due to their capability which can be used in solving wide variety of issues, such as minimize the energy consumption of physical servers, optimize the service cost, improve the quality of experience, increase the service availability, efficiently handle the huge data flow, manages the large number of IoT devices, etc.
Автор: Roy Sudipta, Goyal Lalit Mohan, Mittal Mamta Название: Advanced Prognostic Predictive Modelling in Healthcare Data Analytics ISBN: 9811605408 ISBN-13(EAN): 9789811605406 Издательство: Springer Рейтинг: Цена: 25155.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book discusses major technical advancements and research findings in the field of prognostic modelling in healthcare image and data analysis.
Автор: Dutta, Soumi Название: Data Analytics For Social Microblogging Platforms ISBN: 0323917852 ISBN-13(EAN): 9780323917858 Издательство: Elsevier Science Рейтинг: Цена: 22065.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Salcedo Jesus, McCormick Keith Название: IBM SPSS Modeler Essentials ISBN: 1788291115 ISBN-13(EAN): 9781788291118 Издательство: Неизвестно Рейтинг: Цена: 7171.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: IBM SPSS Modeler allows quick, efficient predictive analytics and insight building from your data, and is a popularly used data mining tool. This book will guide you through the data mining process, and presents relevant statistical methods which are used to build predictive models and conduct other analytic tasks using IBM SPSS Modeler. From ...
Автор: Michael Brackett Название: Data Resource Data: A Comprehensive Data Resource Understanding ISBN: 1935504266 ISBN-13(EAN): 9781935504269 Издательство: Gazelle Book Services Рейтинг: Цена: 8792.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Are you struggling to gain a thorough understanding of your organisations data resource? Are you finding that your data resource has become quite disparate through lack of understanding? Are you having difficulty developing meaningful meta-data about your data resource, or understanding the meta-data that have been developed? Do you agonise over finding a way to document your data resource that is thorough, understandable, and readily available? If the answer to any of these questions is Yes, then you need to read "Data Resource Data" to help you understand your organisations data resource. Most public and private sector organisations do not have a formal process for thoroughly documenting the entire data resource at their disposal, in any meaningful manner, that is readily available to everyone in the organisation. Most do not even have a formal design for that documentation. The much abused, misused, misspelled, undefined, and incomplete meta-data are not providing a denotative understanding of the organisations data resource, without which a high quality data resource cannot be developed. This book provides the complete detailed data resource model for understanding and managing data as a critical resource of the organisation. The model presents formal data resource data as a replacement for the relatively ineffective meta-data. It provides an excellent example of a formal data resource model, compared to a traditional data model, that can be easily implemented by any organisation. The use of data resource data ensures a thorough understanding of an organisations data resource and the development of a high quality comparate data resource. Like "Data Resource Simplexity", "Data Resource Integration" and "Data Resource Design", Michael Brackett draws on five decades of data management experience, in a wide variety of different public and private sector organisations, to understand and document an organisations data resource. He leverages theories, concepts, principles, and techniques from many different and varied disciplines, such as human dynamics, mathematics, physics, chemistry, philosophy, and biology, and applies them to the process of formally documenting an organisations data resource.
Описание: Social Media and the Internet of Things have resulted in an avalanche of data. Data is powerful but not in its raw form; it needs to be processed and modeled, and Python is one of the most robust tools out there to do so. It has an array of packages for predictive modeling and a suite of IDEs to choose from. This book is your guide to getting ...
Описание: This book focuses on automated analytical techniques for healthcare applications used to extract knowledge from a large amount of data. It brings together a variety of different aspects of the healthcare system and aids in the decision-making processes for healthcare professionals.
Автор: Memmert, Daniel Raabe, Dominik Название: Data analytics in football ISBN: 1032532475 ISBN-13(EAN): 9781032532479 Издательство: Taylor&Francis Рейтинг: Цена: 5664.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
As data holdings get bigger and questions get harder, data scientists and analysts must focus on the systems, the tools and techniques, and the disciplined process to get the correct answer, quickly Whether you work within industry or government, this book will provide you with a foundation to successfully and confidently process large amounts of quantitative data.
Here are just a dozen of the many questions answered within these pages:
What does quantitative analysis of a system really mean?
What is a system?
What are big data and analystics?
How do you know your numbers are good?
What will the future data science environment look like?
How do you determine data provenance?
How do you gather and process information, and then organize, store, and synthesize it?
How does an organization implement data analytics?
Do you really need to think like a Chief Information Officer?
What is the best way to protect data?
What makes a good dashboard?
What is the relationship between eating ice cream and getting attacked by a shark?
The nine chapters in this book are arranged in three parts that address systems concepts in general, tools and techniques, and future trend topics. Systems concepts include contrasting open and closed systems, performing data mining and big data analysis, and gauging data quality. Tools and techniques include analyzing both continuous and discrete data, applying probability basics, and practicing quantitative analysis such as descriptive and inferential statistics. Future trends include leveraging the Internet of Everything, modeling Artificial Intelligence, and establishing a Data Analytics Support Office (DASO).
Many examples are included that were generated using common software, such as Excel, Minitab, Tableau, SAS, and Crystal Ball. While words are good, examples can sometimes be a better teaching tool. For each example included, data files can be found on the companion website. Many of the data sets are tied to the global economy because they use data from shipping ports, air freight hubs, largest cities, and soccer teams. The appendices contain more detailed analysis including the 10 T's for Data Mining, Million Row Data Audit (MRDA) Processes, Analysis of Rainfall, and Simulation Models for Evaluating Traffic Flow.
Описание: This book outlines the benefits and limitations of simulation, what is involved in setting up a simulation capability in an organization, the steps involved in developing a simulation model and how to ensure that model results are implemented. In addition, detailed example applications are provided to show where the tool is useful and what it can offer the decision maker. In Simulating Business Processes for Descriptive, Predictive, and Prescriptive Analytics , Andrew Greasley provides an in-depth discussion of Business process simulation and how it can enable business analytics How business process simulation can provide speed, cost, dependability, quality, and flexibility metrics Industrial case studies including improving service delivery while ensuring an efficient use of staff in public sector organizations such as the police service, testing the capacity of planned production facilities in manufacturing, and ensuring on-time delivery in logistics systems State-of-the-art developments in business process simulation regarding the generation of simulation analytics using process mining and modeling people’s behavior Managers and decision makers will learn how simulation provides a faster, cheaper and less risky way of observing the future performance of a real-world system. The book will also benefit personnel already involved in simulation development by providing a business perspective on managing the process of simulation, ensuring simulation results are implemented, and that performance is improved.
Автор: Winters Ralph Название: Practical Predictive Analytics ISBN: 1785886185 ISBN-13(EAN): 9781785886188 Издательство: Неизвестно Рейтинг: Цена: 10114.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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