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Comprendre l'intelligence artificielle (L'Encyclopédie d'Utovie)
Par Louis Belon. 2023
Un ouvrage pour faire toute la lumière sur l'intelligence artificielle qui, selon l'auteur, ne constitue pas un mal en soi…
mais qui nécessite de s'interroger sur celles et ceux qui sont à l'origine de cet outil.Building a cyber risk management program: Evolving security for the digital age
Par Brian Allen. 2024
Cyber risk management is one of the most urgent issues facing enterprises today. This book presents a detailed framework for…
designing, developing, and implementing a cyber risk management program that addresses your company's specific needs. Ideal for corporate directors, senior executives, security risk practitioners, and auditors at many levels, this guide offers both the strategic insight and tactical guidance you're looking for. You'll learn how to define and establish a sustainable, defendable, cyber risk management program, and the benefits associated with proper implementation. Cyber risk management experts Brian Allen and Brandon Bapst, working with writer Terry Allan Hicks, also provide advice that goes beyond risk management. You'll discover ways to address your company's oversight obligations as defined by international standards, case law, regulation, and board-level guidance. This book helps you: understand the transformational changes digitalization is introducing, and new cyber risks that come with it; learn the key legal and regulatory drivers that make cyber risk management a mission-critical priority for enterprises; gain a complete understanding of four components that make up a formal cyber risk management program; and implement or provide guidance for a cyber risk management program within your enterpriseNGINX Cookbook
Par Derek DeJonghe. 2024
NGINX is one of the most widely used web servers available today, in part because of itscapabilities as a load…
balancer and reverse proxy server for HTTP and other network protocols. This revised cookbook provides easy-to-follow examples of real-world problems in application delivery. Practical recipes help you set up and use either the open source or commercial offering to solve problems in various use cases.For professionals who understand modern web architectures, such as n-tier or microservice designs and common web protocols such as TCP and HTTP, these recipes provide proven solutions for security and software load balancing and for monitoring and maintaining NGINX's application delivery platform. You'll also explore advanced features of both NGINX and NGINX Plus, the free and licensed versions of this server.You'll find recipes for:High-performance load balancing with HTTP, TCP, and UDPSecuring access through encrypted traffic, secure links, HTTP authentication subrequests, and moreDeploying NGINX to Google, AWS, and Azure cloudSetting up and configuring NGINX ControllerInstalling and configuring the NGINX App Protect moduleEnabling WAF through Controller ADCNGINX Instance Manager, Service Mesh, and the njs moduleLaws of UX: Using Psychology To Design Better Products And Services
Par Jon Yablonski. 2024
An understanding of psychology-specifically the psychology behind how users behave and interact with digital interfaces-is perhaps the single most valuable…
nondesign skill a designer can have. The most elegant design can fail if it forces users to conform to the design instead of working within the "blueprint" of how humans perceive and process the world around them.This practical guide explains how you can apply key principles of psychology to build products and experiences that are more human-centered and intuitive. Author Jon Yablonski deconstructs familiar apps and experiences to provide clear examples of how UX designers can build interfaces that adapt to how users perceive and process digital interfaces.You'll learn:How aesthetically pleasing design creates positive responsesThe principles of psychology most useful for designersHow these psychology principles relate to UX heuristicsPredictive models including Fitts's law, Jakob's law, and Hick's lawEthical implications of using psychology in designA practical framework for applying principles of psychology in your design processThis updated edition includes an even deeper connection to the underlying psychological concepts that govern the principles explored in the book, along with accompanying UX methods and techniques. Examples have been updated to ensure the deconstructed apps and experiences remain familiar and relevant.Linked: Conquer LinkedIn. Get Your Dream Job. Own Your Future.
Par Omar Garriott, Jeremy Schifeling. 2022
The LinkedIn insider&’s guide to how the new job search really works—and how to make it work for you. No…
one disputes that LinkedIn is the world&’s biggest job market. So it&’s about time that someone with the inside scoop explained how to make the most of it. Here, from two LinkedIn experts and former employees, is the definitive guide that demystifies the massive site and gives every reader—from the newly minted college graduate to the midlife career-changer—the most important strategies to win the modern job search game. Clear, lively, and decidedly practical, Linked shows how to burnish your personal brand so recruiters come to you. Tap the power of the network effect and turn anyone into an invaluable referral. Think like employers and focus your profile to get noticed, get considered, and get hired. And game both the search algorithm and Applicant Tracking Systems used by nearly every employer in every economic sector. The result: not just a great job, but the future of your dreams.Distributed Machine Learning Patterns
Par Yuan Tang. 2024
Practical patterns for scaling machine learning from your laptop to a distributed cluster.Distributing machine learning systems allow developers to handle…
extremely large datasets across multiple clusters, take advantage of automation tools, and benefit from hardware accelerations. This book reveals best practice techniques and insider tips for tackling the challenges of scaling machine learning systems. In Distributed Machine Learning Patterns you will learn how to: Apply distributed systems patterns to build scalable and reliable machine learning projects Build ML pipelines with data ingestion, distributed training, model serving, and more Automate ML tasks with Kubernetes, TensorFlow, Kubeflow, and Argo Workflows Make trade-offs between different patterns and approaches Manage and monitor machine learning workloads at scale Inside Distributed Machine Learning Patterns you&’ll learn to apply established distributed systems patterns to machine learning projects—plus explore cutting-edge new patterns created specifically for machine learning. Firmly rooted in the real world, this book demonstrates how to apply patterns using examples based in TensorFlow, Kubernetes, Kubeflow, and Argo Workflows. Hands-on projects and clear, practical DevOps techniques let you easily launch, manage, and monitor cloud-native distributed machine learning pipelines. About the technology Deploying a machine learning application on a modern distributed system puts the spotlight on reliability, performance, security, and other operational concerns. In this in-depth guide, Yuan Tang, project lead of Argo and Kubeflow, shares patterns, examples, and hard-won insights on taking an ML model from a single device to a distributed cluster. About the book Distributed Machine Learning Patterns provides dozens of techniques for designing and deploying distributed machine learning systems. In it, you&’ll learn patterns for distributed model training, managing unexpected failures, and dynamic model serving. You&’ll appreciate the practical examples that accompany each pattern along with a full-scale project that implements distributed model training and inference with autoscaling on Kubernetes. What's inside Data ingestion, distributed training, model serving, and more Automating Kubernetes and TensorFlow with Kubeflow and Argo Workflows Manage and monitor workloads at scale About the reader For data analysts and engineers familiar with the basics of machine learning, Bash, Python, and Docker. About the author Yuan Tang is a project lead of Argo and Kubeflow, maintainer of TensorFlow and XGBoost, and author of numerous open source projects. Table of Contents PART 1 BASIC CONCEPTS AND BACKGROUND 1 Introduction to distributed machine learning systems PART 2 PATTERNS OF DISTRIBUTED MACHINE LEARNING SYSTEMS 2 Data ingestion patterns 3 Distributed training patterns 4 Model serving patterns 5 Workflow patterns 6 Operation patterns PART 3 BUILDING A DISTRIBUTED MACHINE LEARNING WORKFLOW 7 Project overview and system architecture 8 Overview of relevant technologies 9 A complete implementationInternet of Production: Fundamentals, Methods and Applications (Interdisciplinary Excellence Accelerator Series)
Par Christian Brecher, Günther Schuh, Wil van der Aalst, Matthias Jarke, Frank T. Piller, Melanie Padberg. 2024
This seminal compendium, available through open access, illuminates the forefront of digital collaboration in production. It introduces the visionary concept…
of the Internet of Production (IoP), an ambitious initiative by Germany's esteemed Cluster of Excellence at RWTH Aachen University. This handbook pioneers the integration of data, models, and knowledge across development, production, and user cycles, offering interdisciplinary insights into production technology's horizons with the overall objective to create a worldwide lab.The work is organized into seven key parts, each contributing to a comprehensive understanding of the IoP. Part I lays the foundation with interdisciplinary visions and concepts. Part II delves into IoP's infrastructure, encompassing digital shadows and actionable artificial intelligence. Part III examines materials within the digitalized production landscape. Part IV confronts the challenges and potentials of production processes under novel digitalization methods.Part V focuses on production management with data-driven decision support, while Part VI explores agile development processes. Finally, Part VII delves into the interplay between internal and external perspectives in the IoP, human-centered work design, and platform-based ecosystems.Supported by the German Research Foundation (DFG), this compendium redefines manufacturing through the transformative IoP lens. Embrace this scholarly endeavor to embrace technological advancement. This is an open access book.Learn Concurrent Programming with Go
Par James Cutajar. 2024
Concurrency doesn&’t need to be confusing. Start writing concurrent code that improves performance, scales up to handle large volumes of…
data, and takes full advantage of modern multi-processor hardware.Too many developers think concurrency is extremely challenging. Learn Concurrent Programming with Go is here to prove them wrong! This book uses the easy-to-grasp concurrency tools of the Go language to demonstrate principles and techniques, steadily teaching you the best practices of effective concurrency. Techniques learned in this book can be applied to other languages. In Learn Concurrent Programming with Go you will learn how to: Implement effective concurrency for more responsive, higher performing, scalable software Avoid common concurrency problems such as deadlocks and race conditions Manage concurrency using goroutines, mutexes, readers-writer locks, and more Identify concurrency patterns such as pipelining, worker pools, and message passing Discover advantages, limits, and properties of parallel computing Improve your Go coding skills with advanced multithreading topics Concurrent programming allows multiple tasks to execute and interact simultaneously, speeding up performance and reducing user wait time. In Learn Concurrent Programming with Go, you&’ll discover universal principles of concurrency, along with how to use them for a performance boost in your Go applications. Expert author James Cutajar starts with the basics of modeling concurrency in your programs, demonstrates differences between message passing and memory sharing, and even introduces advanced topics such as atomic variables and futexes. About the technology You can improve almost any application&’s performance and responsiveness by introducing concurrency into the codebase. This book will show you how! It starts with the basics of concurrent programming and builds your skills step by step by exploring scenarios you&’ll face every day as a developer. Author James Cutajar explains each aspect of concurrency in plain language using the intuitive features baked into the Go language. About the book Learn Concurrent Programming with Go provides a practical, hands-on introduction to creating software for modern multiprocessor systems. In it, you&’ll learn how to divide larger programming tasks into independent parts that can run simultaneously. You&’ll use the Go language to implement common concurrency patterns by utilizing readers-writer locks, semaphores, message passing, and memory sharing. The skills you learn will easily transfer to other languages. What's inside Prevent deadlocks and race conditions Go concurrency features like goroutines, mutexes, channels, and more Concurrency patterns including pipelining and worker pools About the reader For programmers with basic knowledge of Go or another C-style language. No experience in concurrent programming required. About the author James Cutajar has been programming for more than 20 years. He&’s an open source contributor, blogger, tech evangelist, Udemy instructor, and author. Table of Contents PART 1 FOUNDATIONS 1 Stepping into concurrent programming 2 Dealing with threads 3 Thread communication using memory sharing 4 Synchronization with mutexes 5 Condition variables and semaphores 6 Synchronizing with waitgroups and barriers PART 2 MESSAGE PASSING 7 Communication using message passing 8 Selecting channels 9 Programming with channels PART 3 MORE CONCURRENCY 10 Concurrency patterns 11 Avoiding deadlocks 12 Atomics, spin locks, and futexesLineare Kirchhoff-Netzwerke: Grundlagen, Analyse und Synthese
Par Reiner Thiele. 2023
Das Buch vermittelt ausgehend von den Grundlagen der Netzwerk-Theorie neuartige Analyse- und Syntheseverfahren für lineare zeitinvariante Kirchhoff-Netzwerke. Hierzu verwendet der…
Autor als Elementarnetzwerke gewöhnliche Widerstände, Kondensatoren und Spulen sowie die sogenannten pathologischen Unternetzwerke Nullator, Norator und Nullor. Der Nullor besteht dabei aus einem Nullator und einem Norator, wird hinsichtlich seines Klemmenverhaltens durch die Belevitch-Darstellung beschrieben und näherungsweise durch einen Operationsverstärker realisiert. Zur Analyse oder Synthese erfolgt die Zerlegung in realisierbare Unternetzwerke mit dem Verfahren der Singulärwert-Zerlegung von Matrizen. Außerdem zeigt Reiner Thiele, wie durch die Applikation von Klemmen-Äquivalenzen praxisrelevante elektrische oder elektronische Schaltungen entstehen.Entrepreneurship der Zukunft: Voraussetzung, Implementierung und Anwendung von Künstlicher Intelligenz im Rahmen datenbasierter Geschäftsmodelle
Par Lars Heim, Sebastian Gerth. 2023
Dieses Buch behandelt die Rolle von Künstlicher Intelligenz (KI) im Kontext der fortlaufenden Digitalisierung und Automatisierung in Unternehmen, um Wertschöpfung zu…
optimieren, neue Geschäftsmodelle zu entwickeln oder bestehende zu transformieren. Untersucht werden Voraussetzungen, Implementierung und Anwendung von KI in datenbasierten Geschäftsmodellen und dabei sowohl Chancen als auch Risiken beleuchtet.Der erste Buchabschnitt konzentriert sich auf die erforderlichen Bedingungen für den erfolgreichen Einsatz von KI. Hierzu zählen die Erfassung und Verarbeitung von Daten, der Aufbau einer robusten IT-Infrastruktur und die Personalschulung. Im zweiten Abschnitt wird die Implementierung von KI diskutiert. Besonderer Fokus liegt dabei auf dem Aufbau und Training von KI-Systemen und deren Integration in bestehende Geschäftsprozesse. Verschiedene Ansätze der KI, wie Machine Learning und Deep Learning, werden erläutert und ihre Anwendungsmöglichkeiten aufgezeigt. Der dritte Abschnitt widmet sich der praktischen Anwendung von KI in verschiedenen Branchen und Geschäftsmodellen. So werden etwa Beispiele aus der Produktion, dem Handel und der Dienstleistungsbranche vorgestellt, um den Einsatz von KI zur Automatisierung von Prozessen, Optimierung von Entscheidungen und Verbesserung von Prognosen zu demonstrieren.Insgesamt bietet das Buch eine umfassende Perspektive auf das Thema KI und liefert in 17 Kapiteln wertvolle Anregungen für Unternehmen, um ihre Zukunftsfähigkeit mit KI zu sichern und von den Möglichkeiten zu profitieren. Die Beiträge von führenden Expert:innen aus unterschiedlichen Disziplinen, mit verschiedenen theoretischen Ansätzen, methodischen Zugängen und empirischen Befunden beleuchten und diskutieren das Thema sehr anschaulich.Winning with Data Science: A Handbook for Business Leaders
Par Howard Steven Friedman, Akshay Swaminathan. 2024
Whether you are a newly minted MBA or a project manager at a Fortune 500 company, data science will play…
a major role in your career. Knowing how to communicate effectively with data scientists in order to obtain maximum value from their expertise is essential. This book is a compelling and comprehensive guide to data science, emphasizing its real-world business applications and focusing on how to collaborate productively with data science teams.Taking an engaging narrative approach, Winning with Data Science covers the fundamental concepts without getting bogged down in complex equations or programming languages. It provides clear explanations of key terms, tools, and techniques, illustrated through practical examples. The book follows the stories of Kamala and Steve, two professionals who need to collaborate with data science teams to achieve their business goals. Howard Steven Friedman and Akshay Swaminathan walk readers through each step of managing a data science project, from understanding the different roles on a data science team to identifying the right software. They equip readers with critical questions to ask data analysts, statisticians, data scientists, and other technical experts to avoid wasting time and money. Winning with Data Science is a must-read for anyone who works with data science teams or is interested in the practical side of the subject.Global Digital Data Governance: Polycentric Perspectives (Routledge Global Cooperation Series)
Par Carolina Aguerre, Malcolm Campbell-Verduyn, Jan Aart Scholte. 2024
This book provides a nuanced exploration of contemporary digital data governance, highlighting the importance of cooperation across sectors and disciplines…
in order to adapt to a rapidly evolving technological landscape. Most of the theory around global digital data governance remains scattered and focused on specific actors, norms, processes, or disciplinary approaches. This book argues for a polycentric approach, allowing readers to consider the issue across multiple disciplines and scales. Polycentrism, this book argues, provides a set of lenses that tie together the variety of actors, issues, and processes intertwined in digital data governance at subnational, national, regional, and global levels. Firstly, this approach uncovers the complex array of power centers and connections in digital data governance. Secondly, polycentric perspectives bridge disciplinary divides, challenging assumptions and drawing together a growing range of insights about the complexities of digital data governance. Bringing together a wide range of case studies, this book draws out key insights and policy recommendations for how digital data governance occurs and how it might occur differently. Written by an international and interdisciplinary team, this book will be of interest to students and scholars in the field of development studies, political science, international relations, global studies, science and technology studies, sociology, and media and communication studies.Handbook of Face Recognition
Par Stan Z. Li, Anil K. Jain, Jiankang Deng. 2024
The history of computer-aided face recognition dates to the 1960s, yet the problem of automatic face recognition – a task…
that humans perform routinely and effortlessly in our daily lives – still poses great challenges, especially in unconstrained conditions.This highly anticipated new edition provides a comprehensive account of face recognition research and technology, spanning the full range of topics needed for designing operational recognition systems. After a thorough introduction, each subsequent chapter focuses on a specific topic, reviewing background information, up-to-date techniques, and recent results, as well as offering challenges and future directions.Topics and features:Fully updated, revised, and expanded, covering the entire spectrum of concepts, methods, and algorithms for automated detection and recognition systemsProvides comprehensive coverage of face detection, alignment, feature extraction, and recognition technologies, and issues in evaluation, systems, security, and applicationsContains numerous step-by-step algorithmsDescribes a broad range of applications from person verification, surveillance, and security, to entertainmentPresents contributions from an international selection of preeminent expertsIntegrates numerous supporting graphs, tables, charts, and performance dataThis practical and authoritative reference is an essential resource for researchers, professionals and students involved in image processing, computer vision, biometrics, security, Internet, mobile devices, human-computer interface, E-services, computer graphics and animation, and the computer game industry.AI and Business, and Innovation Research: Understanding the Potential and Risks of AI for Modern Enterprises (Studies in Systems, Decision and Control #440)
Par Bahaaeddin Alareeni, Islam Elgedawy. 2024
This book provides a comprehensive overview of the latest trends and developments in AI and business innovation research. In today's…
rapidly changing business environment, artificial intelligence (AI) has become an essential tool for innovation and growth. From marketing and customer service to supply chain management and product development, AI is transforming the way businesses operate, allowing them to make better decisions and achieve their goals faster and more efficiently than ever before.However, the integration of AI into business operations is not without its challenges and risks. There are concerns about data privacy, cybersecurity, and the potential for AI to disrupt traditional industries and displace workers. As a result, it is essential for business leaders and researchers to understand both the potential and risks of AI, and how it can be effectively leveraged for business innovation.This book explores the potential benefits of AI for modern enterprises, including how it can be used to enhance customer service, optimize supply chain management, and improve decision-making in a range of business contexts. It also examines the role of AI in product development, marketing, and sales, and how it can be used to drive innovation and growth.The book also examines the risks and challenges associated with the integration of AI into business operations. It explores the ethical and legal implications of AI, including issues related to data privacy and security, bias in algorithms, and the impact of AI on employment and the labor market. It also examines the role of government and policymakers in regulating AI and managing the risks associated with its integration into business operations.Overall, this book provides a comprehensive and balanced perspective on the potential and risks of AI for modern enterprises.Ethics in Artificial Intelligence: Bias, Fairness and Beyond (Studies in Computational Intelligence #1123)
Par Animesh Mukherjee, Juhi Kulshrestha, Abhijnan Chakraborty, Srijan Kumar. 2023
This book is a collection of chapters in the newly developing area of ethics in artificial intelligence. The book comprises…
chapters written by leading experts in this area which makes it a one of its kind collections. Some key features of the book are its unique combination of chapters on both theoretical and practical aspects of integrating ethics into artificial intelligence. The book touches upon all the important concepts in this area including bias, discrimination, fairness, and interpretability. Integral components can be broadly divided into two segments – the first segment includes empirical identification of biases, discrimination, and the ethical concerns thereof in impact assessment, advertising and personalization, computational social science, and information retrieval. The second segment includes operationalizing the notions of fairness, identifying the importance of fairness in allocation, clustering and time series problems, and applications of fairness in software testing/debugging and in multi stakeholder platforms. This segment ends with a chapter on interpretability of machine learning models which is another very important and emerging topic in this area.Geo-Topology: Theory, Models and Applications (GeoJournal Library #133)
Par Fivos Papadimitrou. 2023
Geo-Topology is an exploration of the depth and breadth of the relationships between Geography and Topology, with applications ranging from…
Landscape Geography to Social Geography and from Spatial Analysis to Geospatial Technologies. It shows how topics of geographical research (landscapes, borders, spatial social relationships etc) can be examined by using mathematical concepts and methods of Topology, exposing the realm of geo-topological modelling and visualization through Point-Set Topology, Knot Theory, Reeb graphs, Topological Surfaces (i.e. Möbius bands and Klein bottles), Differential Topology, Network Analysis, Combinatorial Topology, Braid Theory and Ultrametric Topology. Besides geographers, this book is a trove of new ideas for landscape ecologists, mathematicians, data scientists, sociologists, psychologists, anthropologists and educators. Geo-Topology is a systematic introduction to topological thinking in Geography, also by highlighting the significance of Topology for Geographical Education, as well as for the Philosophy and Epistemology of Geography.Digital Transformation: Industry 4.0 to Society 5.0 (Disruptive Technologies and Digital Transformations for Society 5.0)
Par Avadhesh Kumar, Shrddha Sagar, Poongodi Thangamuthu, B. Balamurugan. 2024
This book focuses on computing for Industry 4.0 illustrating different domains with the purpose of integration with existing domains for…
automation of processes. It gives readers an idea about the various challenges and design structure for computing of Industry 4.0. The contents include contributions from experts in Cyber-Physical Systems (CPS), the Internet of Things (IoT), Industrial Internet of Things (IIoT), cloud computing, cognitive computing, and artificial intelligence across the world, contributing their knowledge to identify the different characteristics of the above domains.Frontier Computing on Industrial Applications Volume 3: Proceedings of Theory, Technologies and Applications (FC 2023) (Lecture Notes in Electrical Engineering #1133)
Par Jason C. Hung, Neil Yen, Jia-Wei Chang. 2024
This book gathers the proceedings of the 13th International Conference on Frontier Computing, held in Tokyo, on July 10–13, 2023,…
and provides comprehensive coverage of the latest advances and trends in information technology, science, and engineering. It addresses a number of broad themes, including communication networks, business intelligence and knowledge management, Web intelligence, and related fields that inspire the development of information technology. The respective contributions cover a wide range of topics: database and data mining, networking and communications, Web and Internet of things, embedded systems, soft computing, social network analysis, security and privacy, optical communication, and ubiquitous/pervasive computing. Many of the papers outline promising future research directions, and the book benefits students, researchers, and professionals alike. Further, it offers a useful reference guide for newcomers to the field.Extended Reality: International Conference, XR Salento 2023, Lecce, Italy, September 6-9, 2023, Proceedings, Part I (Lecture Notes in Computer Science #14218)
Par Lucio Tommaso De Paolis, Pasquale Arpaia, Marco Sacco. 2023
This two-volume set LNCS 14218 and LNCS 14219 constitutes the refereed proceedings of the International Conference on Extended Reality, XR…
Salento 2023, held in Lecce, Italy, during September 6-9, 2023. The 60 full papers presented together with 11 short papers were carefully reviewed and selected from 97 submissions. They cover a wide range of many different research topics such as: eXtended reality; digital twin; artificial intelligence; user experience in eXtended reality; virtual reality for neurofeedback, biofeedback and emotion recognition; eXtended reality in education; eXtended reality and metaverse in cultural heritage; eXtended reality in health and medicine; and eXtended reality in industrial field.Grundkurs Geschäftsprozess-Management: Analyse, Modellierung, Optimierung und Controlling von Prozessen
Par Andreas Gadatsch. 2023
Dieses Lehrbuch schlägt die Brücke zwischen den betriebswirtschaftlich-organisatorischen Methoden und deren digitaler Umsetzung, denn Prozessmanagement heißt zunehmend Gestaltung betrieblicher Aufgaben.…
Neben methodischen Grundlagen bietet das Werk viele Praxisbeispiele und Übungen. Das Buch von Prof. Gadatsch gilt mittlerweile als der "aktuelle Klassiker", DAS maßgebliche Standardwerk zur IT-gestützten Gestaltung von Geschäftsprozessen.Die zehnte Auflage wurde überarbeitet und an die Anforderungen der Digitalen Transformation angepasst. Das Prozessmanagement hat sich durch den Trend der Digitalisierung und infolge der Pandemie stark weiterentwickelt. Ein weiterer damit verknüpfter Trend ist die verstärkte Nutzung von Data Science-Methoden für das Prozessmanagement, was auf wissenschaftlichen Konferenzen folgerichtig als "Process Science" bezeichnet wurde. Von besonderer Bedeutung sind auch jüngere Forschungsergebnisse, die unter dem Stichwort „Exploratives Prozessmanagement“ veröffentlicht wurden. Sie zeigen auf, dass die erste Hauptphase des Prozessmanagements eher auf die Optimierung bestehender Prozesse und Geschäftsmodelle ausgerichtet war. An verschiedenen Stellen des Buches wurden neue Praxisbeispiele aufgenommen, so zum Beispiel die Migrationsstrategien für das ERP-System „SAP S/4 HANA“, welches die Basis für viele Industrie- und Dienstleistungsprozesse darstellt. Das Kapitel zur Modellierung von Prozessen wurde aktualisiert und neuere Methoden wie z. B. Business Model Canvas aufgenommen.