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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: Richard Hill
Publisher: Springer Nature
ISBN: 3030791041
Category : Computers
Languages : en
Pages : 285
Get Book
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: Michael Watson
Publisher: Pearson Education
ISBN: 013340742X
Category : Business & Economics
Languages : en
Pages : 253
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Book Description
Analytics and Big Data Demystified, The up-to-the-minute introduction for every manager, Everything you need to know to get results!, Concepts, applications, tools, techniques, and pitfalls to avoid, How to derive more value from tools and data you already own, Want to start leveraging analytics and Big Data for profit? Managerial Analytics is your ideal first resource. Whatever your industry or management role, this up-to-date guide will help you get started fast, get started right, and quickly start driving value. Book jacket.
Author: Shiyu Zhou
Publisher: John Wiley & Sons
ISBN: 1119666309
Category : Mathematics
Languages : en
Pages : 356
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Book Description
Discover data analytics methodologies for the diagnosis and prognosis of industrial systems under a unified random effects model In Industrial Data Analytics for Diagnosis and Prognosis - A Random Effects Modelling Approach, distinguished engineers Shiyu Zhou and Yong Chen deliver a rigorous and practical introduction to the random effects modeling approach for industrial system diagnosis and prognosis. In the book’s two parts, general statistical concepts and useful theory are described and explained, as are industrial diagnosis and prognosis methods. The accomplished authors describe and model fixed effects, random effects, and variation in univariate and multivariate datasets and cover the application of the random effects approach to diagnosis of variation sources in industrial processes. They offer a detailed performance comparison of different diagnosis methods before moving on to the application of the random effects approach to failure prognosis in industrial processes and systems. In addition to presenting the joint prognosis model, which integrates the survival regression model with the mixed effects regression model, the book also offers readers: A thorough introduction to describing variation of industrial data, including univariate and multivariate random variables and probability distributions Rigorous treatments of the diagnosis of variation sources using PCA pattern matching and the random effects model An exploration of extended mixed effects model, including mixture prior and Kalman filtering approach, for real time prognosis A detailed presentation of Gaussian process model as a flexible approach for the prediction of temporal degradation signals Ideal for senior year undergraduate students and postgraduate students in industrial, manufacturing, mechanical, and electrical engineering, Industrial Data Analytics for Diagnosis and Prognosis is also an indispensable guide for researchers and engineers interested in data analytics methods for system diagnosis and prognosis.
Author: Thomas H. Davenport
Publisher: Harvard Business Press
ISBN: 1422177696
Category : Business & Economics
Languages : en
Pages : 231
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Book Description
As a follow-up to the successful Competing on Analytics, authors Tom Davenport, Jeanne Harris, and Robert Morison provide practical frameworks and tools for all companies that want to use analytics as a basis for more effective and more profitable decision making. Regardless of your company's strategy, and whether or not analytics are your company's primary source of competitive differentiation, this book is designed to help you assess your organization's analytical capabilities, provide the tools to build these capabilities, and put analytics to work. The book helps you answer these pressing questions: What assets do I need in place in my organization in order to use analytics to run my business? Once I have these assets, how do I deploy them to get the most from an analytic approach? How do I get an analytic initiative off the ground in the first place, and then how do I sustain analytics in my organization over time? Packed with tools, frameworks, and all new examples, Analytics at Work makes analytics understandable and accessible and teaches you how to make your company more analytical.
Author: Bart Baesens
Publisher: John Wiley & Sons
ISBN: 1118892747
Category : Business & Economics
Languages : en
Pages : 262
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Book Description
The guide to targeting and leveraging business opportunities using big data & analytics By leveraging big data & analytics, businesses create the potential to better understand, manage, and strategically exploiting the complex dynamics of customer behavior. Analytics in a Big Data World reveals how to tap into the powerful tool of data analytics to create a strategic advantage and identify new business opportunities. Designed to be an accessible resource, this essential book does not include exhaustive coverage of all analytical techniques, instead focusing on analytics techniques that really provide added value in business environments. The book draws on author Bart Baesens' expertise on the topics of big data, analytics and its applications in e.g. credit risk, marketing, and fraud to provide a clear roadmap for organizations that want to use data analytics to their advantage, but need a good starting point. Baesens has conducted extensive research on big data, analytics, customer relationship management, web analytics, fraud detection, and credit risk management, and uses this experience to bring clarity to a complex topic. Includes numerous case studies on risk management, fraud detection, customer relationship management, and web analytics Offers the results of research and the author's personal experience in banking, retail, and government Contains an overview of the visionary ideas and current developments on the strategic use of analytics for business Covers the topic of data analytics in easy-to-understand terms without an undo emphasis on mathematics and the minutiae of statistical analysis For organizations looking to enhance their capabilities via data analytics, this resource is the go-to reference for leveraging data to enhance business capabilities.
Author: Shonna D. Waters
Publisher:
ISBN: 9781586445324
Category : Business & Economics
Languages : en
Pages : 0
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Book Description
The need for HR professionals to understand and apply data analytics is greater than ever. Today's successful HR professionals must ask insightful questions, understand key terms, and intelligently apply data, but may lack a clear understanding of the many forms, types, applications, interpretations, and capabilities of HR analytics. HR Analytics provides a practical approach to using data to solve real HR challenges in organizations and demystifies analytics with clear guidelines and recommendations for making the business case, starting an HR analytics function, avoiding common pitfalls, presenting data through visualization and storytelling, and much more.
Author: Thomas H. Davenport
Publisher: Harvard Business Review Press
ISBN: 142218725X
Category : Business & Economics
Languages : en
Pages : 241
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Book Description
A renowned thought-leader and a professor of statistics team up to provide the essential tools for enhancing thinking and decision-making in today's workplace in order to be more competitive and successful. 25,000 first printing.
Author: Gregory S. Nelson
Publisher: John Wiley & Sons
ISBN: 1119425093
Category : Business & Economics
Languages : en
Pages : 464
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Book Description
An evidence-based organizational framework for exceptional analytics team results The Analytics Lifecycle Toolkit provides managers with a practical manual for integrating data management and analytic technologies into their organization. Author Gregory Nelson has encountered hundreds of unique perspectives on analytics optimization from across industries; over the years, successful strategies have proven to share certain practices, skillsets, expertise, and structural traits. In this book, he details the concepts, people and processes that contribute to exemplary results, and shares an organizational framework for analytics team functions and roles. By merging analytic culture with data and technology strategies, this framework creates understanding for analytics leaders and a toolbox for practitioners. Focused on team effectiveness and the design thinking surrounding product creation, the framework is illustrated by real-world case studies to show how effective analytics team leadership works on the ground. Tools and templates include best practices for process improvement, workforce enablement, and leadership support, while guidance includes both conceptual discussion of the analytics life cycle and detailed process descriptions. Readers will be equipped to: Master fundamental concepts and practices of the analytics life cycle Understand the knowledge domains and best practices for each stage Delve into the details of analytical team processes and process optimization Utilize a robust toolkit designed to support analytic team effectiveness The analytics life cycle includes a diverse set of considerations involving the people, processes, culture, data, and technology, and managers needing stellar analytics performance must understand their unique role in the process of winnowing the big picture down to meaningful action. The Analytics Lifecycle Toolkit provides expert perspective and much-needed insight to managers, while providing practitioners with a new set of tools for optimizing results.
Author: Lawrence Maisel
Publisher: John Wiley & Sons
ISBN: 1118240154
Category : Business & Economics
Languages : en
Pages : 276
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Book Description
Discover the breakthrough tool your company can use to make winning decisions This forward-thinking book addresses the emergence of predictive business analytics, how it can help redefine the way your organization operates, and many of the misconceptions that impede the adoption of this new management capability. Filled with case examples, Predictive Business Analytics defines ways in which specific industries have applied these techniques and tools and how predictive business analytics can complement other financial applications such as budgeting, forecasting, and performance reporting. Examines how predictive business analytics can help your organization understand its various drivers of performance, their relationship to future outcomes, and improve managerial decision-making Looks at how to develop new insights and understand business performance based on extensive use of data, statistical and quantitative analysis, and explanatory and predictive modeling Written for senior financial professionals, as well as general and divisional senior management Visionary and effective, Predictive Business Analytics reveals how you can use your business's skills, technologies, tools, and processes for continuous analysis of past business performance to gain forward-looking insight and drive business decisions and actions.
Author: Bill Franks
Publisher: John Wiley & Sons
ISBN: 1118976762
Category : Business & Economics
Languages : en
Pages : 304
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Book Description
Lead your organization into the industrial revolution of analytics with The Analytics Revolution The topics of big data and analytics continue to be among the most discussed and pursued in the business world today. While a decade ago many people still questioned whether or not data and analytics would help improve their businesses, today virtually no one questions the value that analytics brings to the table. The Analytics Revolution focuses on how this evolution has come to pass and explores the next wave of evolution that is underway. Making analytics operational involves automating and embedding analytics directly into business processes and allowing the analytics to prescribe and make decisions. It is already occurring all around us whether we know it or not. The Analytics Revolution delves into the requirements for laying a solid technical and organizational foundation that is capable of supporting operational analytics at scale, and covers factors to consider if an organization is to succeed in making analytics operational. Along the way, you'll learn how changes in technology and the business environment have led to the necessity of both incorporating big data into analytic processes and making them operational. The book cuts straight through the considerable marketplace hype and focuses on what is really important. The book includes: An overview of what operational analytics are and what trends lead us to them Tips on structuring technology infrastructure and analytics organizations to succeed A discussion of how to change corporate culture to enable both faster discovery of important new analytics and quicker implementation cycles of what is discovered Guidance on how to justify, implement, and govern operational analytics The Analytics Revolution gives you everything you need to implement operational analytic processes with big data.
