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This book addresses data quality management for data markets, including foundational quality issues in modern data science. By clarifying the concept of data quality, its impact on real-world applications, and the challenges stemming from poor data quality, it will equip data scientists and engineers with advanced skills in data quality management, with a particular focus on applications within data markets. This will help them create an environment that encourages potential data sellers with high-quality data to join the market, ultimately leading to an improvement in overall data quality. High-quality data, as a novel factor of production, has assumed a pivotal role in driving digital economic development. The acquisition of such data is particularly important for contemporary decision-making models. Data markets facilitate the procurement of high-quality data and thereby enhance the data supply. Consequently, potential data sellers with high-quality data are incentivized to enter the market, an aspect that is particularly relevant in data-scarce domains such as personalized medicine and services. Data scientists have a pivotal role to play in both the intellectual vitality and the practical utility of high-quality data. Moreover, data quality control presents opportunities for data scientists to engage with less structured or ambiguous problems. The book will foster fruitful discussions on the contributions that various scientists and engineers can make to data quality and the further evolution of data markets.

Entdecken Sie'Enterprise Architektur entschlüsselt: Ein praxisorientierter Leitfaden von den Grundlagen bis zur Anwendung“ von Dennis Suhari, ein praxisorientiertes Werk, das die Förderung des Bewusstseins für Enterprise Architektur, die Vermittlung praktischer Erfahrungen und die Unterstützung der Leser bei der erfolgreichen Anwendung ihres Wissens in den Mittelpunkt stellt. Ein Schlüsselelement dieses Buches ist das praxisnahe Fallbeispiel, das einen einzigartigen Einblick in den Aufbau einer Enterprise Architektur von der Geschäfts- über die IT Architektur von Grund auf bietet.Was Sie erwartet:Fundamentale Grundlagen: Ein tiefgreifender Einblick in die essenziellen Grundlagen der Unternehmensarchitektur, um Schlüsselkonzepte und Prinzipien zu vermitteln, die als robuste Basis für die weitere Entwicklung dienen.Modellierung und praktische Tools: Entdecken Sie vielfältige Modellierungsmöglichkeiten und EAM-Tools, die inder Praxis zur Unterstützung der Architekturentwicklung eingesetzt werden.Architekturentwicklung in der Praxis: Anhand des Fallbeispiels der fiktiven Micayu GmbH, basierend auf den umfangreichen Erfahrungen des Autors, erleben Sie die Schritte der Entwicklung einer Unternehmensarchitektur von Grund auf.Zukunftsperspektiven: Ein Ausblick auf die Rolle der Künstlichen Intelligenz und dessen Einfluss auf das Enterprise Architektur Management

Mit diesem Buch erhalten Sie kompaktes Wissen zur Ausrichtung der IT an den Geschäftserfordernissen:-Geschäftstreiber verstehen und nachvollziehbar dokumentieren-Systematisch Anforderungen an die IT ableitenMit dem Ziel-Bild vor Augen und der Roadmap für die Umsetzung gestalten Sie die digitale Transformation – vom Business bis zur technischen Umsetzung. Schaffen Sie so die organisatorischen Voraussetzungen für die strategische IT-Planung. Dashboards und KPIs zur wirksamen Steuerung der Umsetzung der Planung sind dabei wichtige Hilfsmittel. Ein Schritt-für-Schritt-Leitfaden und ein ausführliches Glossar unter-stützen Sie bei Ihrer Arbeit.

This open access book presents a rich set of innovative solutions for artificial intelligence (AI) in manufacturing. The various chapters of the book provide a broad coverage of AI systems for state of the art flexible production lines including both cyber-physical production systems (Industry 4.0) and emerging trustworthy and human-centered manufacturing systems (Industry 5.0). From a technology perspective, the book addresses a wide range of AI paradigms such as deep learning, reinforcement learning, active learning, agent-based systems, explainable AI, industrial robots, and AI-based digital twins. Emphasis is put on system architectures and technologies that foster human-AI collaboration based on trusted interactions between workers and AI systems. From a manufacturing applications perspective, the book illustrates the deployment of these AI paradigms in a variety of use cases spanning production planning, quality control, anomaly detection, metrology, workers'training, supply chain management, as well as various production optimization scenarios. This is an open access book.

The emergence of Artificial Intelligence (AI) has had a tremendous impact on embedded and mobile systems. This book presents a diverse collection of papers that showcase cutting-edge research and practical applications of AI in this field. The peer-reviewed research articles stem from the First International Conference on Embedded and Mobile Systems (ICTA-EMOS), which was held on November 24th – 25th, 2022, in Arusha, Tanzania, East Africa. They demonstrate the breadth and depth of AI's impact across various domains, exploring topics such as healthcare advances, transportation optimization, sustainable solutions, and business and process optimization.

This book focuses on the personalisation of the user interface in e-commerce based on collected data on customer behaviour. While product recommendation systems are widely used for this purpose today, they do not allow for a comprehensive adaptation of the layout to different user groups. The proposed approach is based on the conclusion that since e-commerce customers are different, the user interface should also be different. To make this possible, several components need to be combined, which together allow the design of the online shop to be automatically or expertly adapted to the customer's choices and behaviour. It presents and discusses a framework that allows data to be collected, processed and used to optimise UI variants for generated customer segments. The proposed approach has been verified in practice and further developed on this basis, so that the reader is presented with a solution that is not riddled with'baby age'problems, and the limitations and challenges identified are described and commented on in detail. Typical e-commerce systems currently have a single UI for all customers. The implementation of multi-variant UIs therefore represents an opportunity for companies to create a marketing advantage by addressing the personalisation trends in e-commerce.The book is intended for those responsible for developing e-commerce platform and user interfaces for web-based systems, as well as individuals interested in practical applications of machine learning in business.

The book shows application potentials of artificial intelligence in various industries and presents application scenarios on how a practical implementation can take place. The starting point is the description of legal aspects, which includes a European regulation for artificial intelligence and addresses the question of the permissibility of automated decisions. The description of various application potentials, mostly industry-related, and the presentation of some application scenarios form the focus of the topic volume. The book is based on the question of how artificial intelligence can be used in entrepreneurial practice. It offers important information that is just as relevant for practitioners as for students and teachers. This book is a translation of an original German edition. The translation was done with the help of artificial intelligence (machine translation by the service DeepL.com). A subsequent human revision was done primarily in terms of content, so that the book will read stylistically differently from a conventional translation.

This volume is a collection of papers on emerging concepts, significant insights, and novel approaches to Information Systems Development (ISD). It delves into the latest trends in ISD and examines how organizational goals, structure, and the business environment--including regulations and societal trends--can impact the creation and implementation of information systems. The book draws on invited papers selected from the proceedings of the 31st International Conference on Information Systems Development hosted by Instituto Superior Técnico, Lisbon, Portugal, on August 30-September 1, 2023 (ISD2023).The general theme of ISD2023 was'Information Systems Development, Organizational Aspects, and Societal Trends'. This volume is specifically designed for researchers who are interested in exploring the methodological and operational perspectives of Information Systems Development, as well as the impact of organizational aspects and societal trends.The primary target audience for this volume is those who want to deepen their understanding of ISD from both theoretical and practical perspectives.

The book conveys current approaches to digitization in companies and shows how digitization projects can be successfully and safely implemented in practice. Based on the description of a changing value creation and working world, the changes associated with digitization are explained using application scenarios: New business models and business processes are being established, the development of products is changing as is the interaction with customers, new opportunities but also new risks are emerging. The authors of the article present the basics as well as concepts for the concrete planning and implementation of the digitization of processes and applications. Aspects of IT security are not neglected either. The editors'work is based on questions from entrepreneurial practice and is also suitable for students and teachers.

This book constitutes revised papers from the International Workshops held at the 21st International Conference on Business Process Management, BPM 2023, in Utrecht, The Netherlands, during September 2023.Papers from the following workshops are included:• 7th International Workshop on Artificial Intelligence for Business Process Management (AI4BPM 2023)• 7th International Workshop on Business Processes Meet Internet-of-Things (BP-Meet-IoT 2023)• 19th International Workshop on Business Process Intelligence (BPI 2023)• 16th International Workshop on Social and Human Aspects of Business Process Management (BPMS2 2023)• 2nd International Workshop on Data-Driven Business Process Optimization (BPO 2023)• 11th International Workshop on Declarative, Decision and Hybrid Approaches to Processes (DEC2H 2023)• 1st International Workshop on Digital Twins for Business Processes (DT4BP 2023)• 1st International Workshop on Formal Methods for Business Process Management (FM-BPM 2023) • 2nd International Workshop on Natural Language Processing for Business Process Management (NLP4BPM 2023)• 1st International Workshop on Object-Centric Processes from A to Z (OBJECTS 2023)• 3rd International Workshop on Change, Drift, and Dynamics of Organizational Processes (ProDy 2023) Each of the workshops focused on particular aspects of business process management. Overall, after a thorough review process, 42 full papers were selected from a total of 86 submissions.

This book (Volume 1) includes peer reviewed articles from the 5th International Conference on Data Science, Machine Learning and Applications, 2023, held at the G Narayanamma Institute of Technology and Sciences, Hyderabad on 15-16th December, India. ICDSMLA is one of the most prestigious conferences conceptualized in the field of Data Science & Machine Learning offering in-depth information on the latest developments in Artificial Intelligence, Machine Learning, Soft Computing, Human Computer Interaction, and various data science & machine learning applications. It provides a platform for academicians, scientists, researchers and professionals around the world to showcase broad range of perspectives, practices, and technical expertise in these fields. It offers participants the opportunity to stay informed about the latest developments in data science and machine learning.

Responding to the escalating demands placed on organizations and enterprises as they navigate the intricacies of cloud economics, this book offers pragmatic insights for establishing a sturdy foundation for cloud cost management. Scaling Cloud FinOps empowers you with the knowledge and strategies to harness efficient cloud technology usage to proficiently manage cloud costs, refine expenditure, and implement robust, scalable Cloud FinOps practices. At the same time, it arms engineering leaders and executives with the necessary tools to foster a culture of cost awareness critical to greater profitability. At the heart of the book lies author Sasi Kanumuri's #Piggy-Bank Framework, an innovative approach to cloud cost governance that offers a practical blueprint to streamline cost reporting, provisioning, and resource management through automation, efficiency, and overall financial performance. You'll also delve into the intricacies of the 6-factor formula, a proven approach to cloud cost management. From resource rightsizing and cost allocation models to automated guardrails and vendor management, each factor serves as a pillar to support your organization's financial goals. Looking beyond numbers, Scaling Cloud FinOps will give you the tools needed to orchestrate a cultural shift that can permeate every aspect of your organization. You'll learn how to cultivate a cost-aware engineering culture in which financial policies give every team member the knowledge and motivation to make data-driven decisions that drive efficiency, unlocking significant cost savings and cloud financial excellence. What You Will Learn Cultivate a culture of cost awareness and accountability within engineering teams, fostering collaboration and data-driven decision-making to enhance cloud efficiency Best practices from FinOps pioneers who've scaled world-class FinOps Teams at tech giants and startups Explore unique frameworks enriched with real-world case studies, providing invaluable insights into effective cloud cost management (CCM) Acquire expert techniques in cost optimization, automation, and vendor management, all proven to deliver significant savings and optimal efficacy Who This Book Is For Professionals and leaders across the cloud, IT, finance, and procurement industries interested in streamlining cloud expenditures, cultivating a culture of cost awareness across the organization, and establishing robust cloud cost management strategies. Whether you're a novice or seasoned in FinOps practices, this book equips you with the tools to maximize the business value of your cloud investments.

This book presents selected proceedings of the International Conference on Business Analytics in Practice (ICBAP2024), which was held on January 8–11, 2024, at the University of Sharjah, UAE. The book presents advanced modeling and examples to explore the practical applications of business analytics across various industries and domains. In addition, it dives deep into the world of data-driven decision-making, showcasing real-world case studies and best practices to illustrate how organizations can harness the power of analytics to optimize their decision-making processes. From descriptive analytics to predictive modeling and prescriptive analytics, readers will gain valuable insights into the different techniques and methodologies employed in business analytics.

This book focuses on the utilization of GoldenGate Services (GGS) in conjunction with a microservices architecture on the Oracle cloud (OCI), primarily for data migration and integration across various data sources and targets.The book begins with a practical example of utilizing GGS on a Marketplace VM, progressively advancing to in-depth discussions on implementing GoldenGate as a Service on OCI. The book offers illustrative guides for data replication between RDBMSs (such as Oracle, Postgres, and big data targets such as Kafka). Additionally, it explores monitoring techniques using Enterprise Manager and Grafana dashboards. A comparative analysis is presented between traditional VM-based GoldenGate installations and the OCI service model. Special attention is given to Zero Downtime Migration (ZDM) and leveraging GGS for database migration from on-premises to OCI. Some chapters address multi-cloud replication using OCI GGS and include real-life case studies.By the end of this book you will have gained comprehensive insights into the architectural design of GoldenGate Services and will be adept at replicating data using GGS, enabling you to replicate setups in your own environments.What You Will LearnSet up GoldenGate Services for high availability (HA), disaster recovery (DR), migration of data to cloud, and moving data into the data lake or lakehousePerform logical migration of data to the cloud using the ZDM tool (ZDM uses GoldenGate internally).Replicate data to big data targetsMonitor GGS using Enterprise Manager and GrafanaReplicate data in a multi-cloud environment Who This Book Is ForOracle database administrators who want to replicate data or use Oracle GoldenGate Services for migration and setup of high availability (HA) and disaster recovery (DR); and data engineers who want tobuild the data warehouse, data lake, data lakehouse to push data in near real-time

This book includes peer reviewed articles from the 5th International Conference on Data Science, Machine Learning and Applications, 2023, held at the G Narayanamma Institute of Technology and Sciences, Hyderabad on 15-16th December, India. ICDSMLA is one of the most prestigious conferences conceptualized in the field of Data Science & Machine Learning offering in-depth information on the latest developments in Artificial Intelligence, Machine Learning, Soft Computing, Human Computer Interaction, and various data science & machine learning applications. It provides a platform for academicians, scientists, researchers and professionals around the world to showcase broad range of perspectives, practices, and technical expertise in these fields. It offers participants the opportunity to stay informed about the latest developments in data science and machine learning.

This book constitutes selected papers from the 20th European, Mediterranean, and Middle Eastern Conference, EMCIS 2023, which was held in Dubai, UAE, during December 11-12, 2023. EMCIS covers technical, organizational, business, and social issues in the application of information technology and is dedicated to the definition and establishment of Information Systems (IS) as a discipline of high impact for IS professionals and practitioners. It focuses on approaches that facilitate the identification of innovative research of significant relevance to the IS discipline following sound research methodologies that lead to results of measurable impact. The 43 papers presented in this volume were carefully reviewed and selected from a total of 126 submissions. They were organized in topical sections as follows: Part I: Metaverse; blockchain technology and applications; digital governance; healthcare information systems; artificial intelligence; Part II: Big data and analytics; digital services and social media; innovative research projects; managing information systems; smart cities.

Die Digitalisierung und Entwicklungen im Gebiet der künstlichen Intelligenz haben in den letzten Jahren erhebliche Veränderungen in der Gesellschaft und der Unternehmenspraxis hervorgerufen. Aufkommende Technologien in den Feldern Big Data und Advanced Analytics werden auch im Controlling zunehmend diskutiert oder bereits eingesetzt. Dabei befinden sich der Wissensstand, inwieweit Big Data und Advanced Analytics das Controlling beeinflussen und verändern können, und die praktische Anwendung noch in einem frühen Stadium. Diese Arbeit befasst sich deshalb mit der Untersuchung der möglichen Auswirkungen von Big Data und Advanced Analytics im Controlling. Vor diesem Hintergrund werden die Einflüsse dieser digitalen Trends auf den Informationsversorgungsprozess des Controllings, auf die Erfüllung Controlling-spezifischer Anforderungen an Informationen und auf das Forecasting, die Budgetierung und die strategische Planung analysiert. Ferner werden praxisrelevante Herausforderungen, Grenzen und Risiken bei der Implementierung und Nutzung identifiziert sowie Implikationen zu deren Umgang zur Ausschöpfung der Potenziale abgeleitet.

This book presents selected proceedings of DEA45: International Conference on Data Envelopment Analysis, which was held September 4-6, 2023, at Surrey Business School, University of Surrey, Guildford, UK. It contains theoretical and empirical papers on Data Envelopment Analysis (DEA) and related fields with a focus on performance measurement and management. It discusses the latest research and developments and their application in various areas such as regulation, agriculture, education, financial and health services. The book is of interest to both researchers and practitioners working on or utilizing the DEA method for examining efficiencies across various organizations.

Eine immer mehr digital vernetzte Welt führt zu einer sehr großen Menge von unterschiedlichen Daten, die in Echtzeit generiert werden („Big Data“). Ein großer Teil dieser Datenproduzenten sind Nutzer von Social Media oder auch smarten Geräten, wie bspw. Fitnesstrackern oder mit dem Internet verbundenen Waschmaschinen („IoT“). Unternehmen, die sich diese Daten aus der direkten Lebenswelt der Konsumenten zu Nutze machen, können sehr präzise Einblicke bspw. über Einstellungen, Verhalten oder auch die Bedürfnisse potenzieller Kunden erhalten, wodurch der Weg zu einer „automatisierten Vermarktung“ geebnet wird. Zielsetzung dieses Buches ist die Entwicklung eines Konzeptes für ein Autonomous Consumer Business (ACB), das als maximal eigenständig agierendes und durch Künstliche Intelligenz getragenes Geschäftsmodell verstanden wird, bei dem Unternehmen die Bedürfnisse auf der Konsumentenseite automatisch erkennen und durch entsprechende Leistungsangebote befriedigen können. Weiterhin werden zentrale Bestimmungsgrößen, welche die konsumentenseitige Inanspruchnahme eines ACB im besonderen Maße beeinflussen, sowie potenzielle Kundengruppen empirisch identifiziert, wodurch Hinweise zur konkreten Ausgestaltung eines ACB gewonnen werden können.

This book constitutes selected papers from the 20th European, Mediterranean, and Middle Eastern Conference, EMCIS 2023, which was held in Dubai, UAE, during December 11-12, 2023. EMCIS covers technical, organizational, business, and social issues in the application of information technology and is dedicated to the definition and establishment of Information Systems (IS) as a discipline of high impact for IS professionals and practitioners. It focuses on approaches that facilitate the identification of innovative research of significant relevance to the IS discipline following sound research methodologies that lead to results of measurable impact. The 43 papers presented in this volume were carefully reviewed and selected from a total of 126 submissions. They were organized in topical sections as follows: Part I: Metaverse; blockchain technology and applications; digital governance; healthcare information systems; artificial intelligence; Part II: Big data and analytics; digital services and social media; innovative research projects; managing information systems; smart cities.

This book has unique features that set it apart from conventional books on the prevention of system failures in that it provides a method that views human activities from a meta-methodological perspective based upon an inter-disciplinary understanding of human activities. With these characteristics, the book also proposes a common methodological basis to apply to various problems surrounding society today such as an aging social infrastructure; the safety of food, medicine, and public transportation; and the creation of sustainable electricity and cybersecurity. Furthermore, since the failure of human activities is expressed in a three-dimensional space and the topological metrics are implemented, the failure trajectories can be quantitatively monitored in time series to take effective preventive measures. Considering the implementation of the topological metrics, the causes of each failure are classified into two dimensions of the degree of coupling between system elements and theinteraction between the target system and the external environment. Owing to the nature of the introduction of topological metrics, all individual and diverse systems can share general topological metrics. Consequently, understanding various failures over cross-industries is possible with the use of common meta-systemic language and mutual learning between different industries, and the solution of social problems can be effectively achieved. A system of system failures (SOSF) proposed and confirmed the effectiveness of this meta-methodology for information and communication technologies (ICT) systems and the SOSF is extended to human activity systems (SOHAS: system of human activity systems) as a whole. Therefore, the SOHAS becomes an academic foundation for theoretical research on meta-methodology, and it has an impact on practitioners to prevent system failures by accumulating knowledge of failures and learning from other industries.

Most existing companies struggle currently because they lack the tools and strategies to move product departments into independent platforms that can be retrofitted to form dynamic new products based on consumer demands. This book provides managers and professionals with the necessary approaches for designing software and hardware architectures to support data platform organizations. Specifically, it demonstrates how to automate the decomposition of existing platforms into smaller parts that can be reused to form new variations. This task requires significant analysis and design methodologies and procedures to create an infrastructure based on data as opposed to products. These new knowledge bases allow data-centric professionals to pursue actions that can better predict and respond to the unexpected. Featuring case examples from companies such as Lego, FedEx, General Electric (GE), Pfizer, P&G and more, this book is appropriate for C-level executives engagedin the digital transformation of their firms; entrepreneurs of digital platform companies; and senior software engineers that need to design Internet of Things (IoT) devices and integrate them with block chain and multi-cloud architectures. In addition, this book is also useful for graduate-level coursework in data science.

This book discusses advanced technological solutions in Industry 5.0 that can be used for business competitive advantage and sustainability. The book presents tools that can help reduce time and make use of data in an efficient way while using resources efficiently and sustainably. The book aims to highlight technological sustainability through promoting innovations, improving social development, and providing green products that benefit the society. The authors discuss the recent technological advancements such as Artificial Intelligence (AI), Internet of Things (IoT), Financial Technology (FinTech), Big Data, and Blockchain. They also discuss the benefits of incorporating such technologies in areas such as green supply chain, storage technology, Internet banking, and nanotechnology. The target audience of this book includes all interested individuals and institutions in the fields of engineering, business, technology, and public services. The book provides insights and solutions to many issues and creates opportunities for further sustainability.

This book constitutes revised papers from the International Workshops held at the 20th International Conference on Business Process Management, BPM 2022, in Münster, Germany, during September 11-15, 2022. Papers from the following workshops are included:· 6th International Workshop on Artificial Intelligence for Business Process Management (AI4BPM 2022)· 6th International Workshop on Business Processes Meet Internet-of-Things (BP-Meet-IoT 2022)· 18th International Workshop on Business Process Intelligence (BPI 2022)· 2nd International Workshop on Business Process Management and Routine Dynamics (BPM&RD 2022)· 14th International Workshop on Social and Human Aspects of Business Process Management (BPMS2 2022) · 1st International Workshop on Data-Driven Business Process Optimization (BPO 2022) · 10th International Workshop on DEClarative, DECision and Hybrid approaches to processes (DEC2H 2022) · 1st International Workshop on Natural Language Processing for Business Process Management (NLP4BPM 2022) Each of the eight workshops focused on particular aspects of business process management. Overall, after a thorough review process, there were 23 full and 3 short papers selected from a total of 51 submissions. Only one of the short papers is included in the proceedings.

This book gathers selected high-impact articles from the 3rd International Conference on Data Science, Machine Learning & Applications 2021. It highlights the latest developments in the areas of artificial intelligence, machine learning, soft computing, human–computer interaction and various data science and machine learning applications. It brings together scientists and researchers from different universities and industries around the world to showcase a broad range of perspectives, practices and technical expertise.

This book constitutes the refereed post-conference proceedings of the 24th International Conference on Enterprise Information Systems, ICEIS 2022, This conference was held virtually due to the COVID-19 crisis, during April 25-27, 2022.The 20 full papers included in this book were carefully reviewed and selected from 197 submissions. They were organized in topical sections as follows: Databases and Information Systems Integration; Artificial Intelligence and Decision Support Systems; Information Systems Analysis and Specification; Human-Computer Interaction; and Enterprise Architecture.

This book constitutes the proceedings of the 15th PLAIS EuroSymposium on Digital Transformation, PLAIS EuroSymposium 2023, which took place in Sopot, Poland, in September 2023. The primary objective of the PLAIS EuroSymposium 2023 was to foster discussions on general issues pertaining to digital transformation and related topics. The papers selected this year are related to the use of machine learning, internet of things and social media. The 7 full papers included in this volume were carefully reviewed and selected from a total of 22 submissions.

Chatbots sind eine vielversprechende Form der Kommunikation – jedoch schaffen es bisher nur wenige echten Mehrwert zu bieten. In diesem Praxisleitfaden lernen Sie Schritt für Schritt den gesamten Prozess der Chatbot-Entwicklung kennen: Von der Definition des Use Case über die Persönlichkeit des Chatbots und die Modellierung des Dialogablaufs bis hin zu Pilotbetrieb und Roll-Out. Sie erfahren für jeden Schritt, welche Strategien sich bewährt haben und was bei der Umsetzung besonders zu beachten ist. Einen Schwerpunkt bildet das Conversation Design, denn es ist entscheidend für eine gelungene User Experience, für Akzeptanz und langfristigen Erfolg des Chatbots. Anhand zahlreicher Fallbeispiele aus der Praxis und mit klar formulierten Handlungsempfehlungen zeigen die Autorinnen ganz konkret, wie erfolgreiche Chatbots gelingen.Der Inhalt• Bedarfsanalyse, Use Case und User Stories• Planung der Chatbot-Entwicklung• Chatbot-Persönlichkeit und Conversational Experience• Conversation Design, Proof-of-Concept und Prototyping• Dialogablauf und Copywriting • Implementierung, Finetuning und Roll-Out• Evaluation und Continuous Improvement

Data has become an indispensable success factor for every company. However, the road towards a data-driven organization is paved with numerous challenges. This book presents a process model for the path to a data-driven company and provides recommendations for the design of all relevant fields of action: Which structures need to be created? Which systems and processes have proven beneficial? How can the quality of the data be ensured and what requirements exist for a data-driven organization in the areas of governance and communication? And last but not least: How can employees be brought along on the journey and what implications does the data-driven organization have for our corporate culture? The book presents an orientation and action framework for the strategic and operational design of a data-driven organization and is valuable for managers who are involved in data management in companies and organizations.

Der steigende Stellenwert von Daten als Ressource und die zunehmende Ausweitung des Aufgabenspektrums der IT-basierten Entscheidungsunterstützung verändern die logischen Architekturen analytischer Informationssysteme. Insbesondere die Datenhaltungen entwickeln sich vermehrt von zentralen Konstrukten hin zu dezentralen Konglomeraten verschiedenster Speicheransätze. Die zunehmend heterogenen Technologien und die häufig unzureichenden Erfahrungen mit neuartigen Konzepten erhöhen die Komplexität in der Planung und dem Betrieb analytischer Systemlandschaften. Das Ziel dieser Arbeit ist daher die Konzeption eines IT-basierten Entscheidungsunterstützungssystems für die Gestaltung dezentraler Datenhaltungen in analytischen Informationssystemen. Es wird ein Fachkonzept für die Überführung von Architekturansätzen aus realen Umgebungen in abstrahierte Architekturmuster sowie für die fallspezifische Ableitung von Handlungsempfehlungen entwickelt, prototypisch als Software-Werkzeug implementiertund evaluiert. Das hierbei entwickelte Verständnis eines Architekturmusters ermöglicht durch die Kombination von fachlichen-orientierten analytischen Capabilitites und technischen Aspekten eine ganzheitliche und systematische Unterstützung von IT-Architekturentscheidungen.

This book constitutes the refereed proceedings of the 27th International Conference on Enterprise Design, Operations, and Computing, EDOC 2023, held in Groningen, The Netherlands, during October 30–November 3, 2023.The 12 full papers included in this book were carefully reviewed and selected from 36submissions. They were organized in topical sections as follows: Enterprise Modeling, Enterprise Architecture & Engineering, Model-Based Software Engineering, Enterprise Analysis with Process Mining, Process Improvement & Engineering, and Modeling in an Enterprise Context.

This textbook will delve into the philosophical foundation of contemporary IS research design with particular emphasis on the methodological tools that can be applied to conduct effective research in the multidisciplinary area of contemporary IS. What sets the book apart is that it will cover the current social paradigm shift, global changes and the need for new methodological tools, which have revolutionised the way we use IS to support our daily practices. It considers the entire methodological procedures applied to research projects that investigate or explore multifaceted areas of contemporary IS, such as information management, digital business, ICT and information science.Featuring learning objectives, case studies, assessment questions and exercises, this textbook offers a practical outline for IS research methodology that will be of use to students and researchers. It aims to satisfy researchers who are seeking literature on applying methodological procedures to their research projects that delve into the world of contemporary IS that other titles have only considered in a much broader sense.

This volume is a collection of papers on emerging concepts, significant insights, and novel approaches on information systems development (ISD). It examines and investigates up-and-coming trends in ISD in general, emphasizing benefits and risks of Artificial Intelligence in the development and operation of Information Systems. The book draws on invited papers selected from the proceedings of the 30th International Conference on Information Systems Development hosted by Babeș-Bolyai University, Cluj-Napoca, Romania, August 31 - September 2, 2022 (ISD2022). The theme of ISD2022 was “Artificial Intelligence for Information Systems Development and Operations”. The conference focused on the interplay between Information Systems and Artificial Intelligence, trying to emphasize novel, smarter automation approaches and the mitigation of risks related to AI adoption. Primary readership of the volume are researchers interested in methodological and operational perspectives related to ISD in general, and to AI adoption as a means of digital transformation in particular.

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.

This book includes peer reviewed articles from the 4th International Conference on Data Science, Machine Learning and Applications, 2022, held at the Hyderabad Institute of Technology & Management on 26-27th December, India. ICDSMLA is one of the most prestigious conferences conceptualized in the field of Data Science & Machine Learning offering in-depth information on the latest developments in Artificial Intelligence, Machine Learning, Soft Computing, Human Computer Interaction, and various data science & machine learning applications. It provides a platform for academicians, scientists, researchers and professionals around the world to showcase broad range of perspectives, practices, and technical expertise in these fields. It offers participants the opportunity to stay informed about the latest developments in data science and machine learning.

This book includes peer-reviewed contributions presented at the International Conference on Data Analytics in Business and Marketing, ICDABM 2022. The book covers topics in data analytics, intelligent data, data management in business and marketing, big data, computational intelligence, and communication networks. The book presents innovative work by leading academics, researchers, and experts from the industry, which is helpful for young researchers and students.

This book offers a comprehensive collection of research articles that utilize data—in particular large data sets—in modern power systems operation and planning. As the power industry moves towards actively utilizing distributed resources with advanced technologies and incentives, it is becoming increasingly important to benefit from the available heterogeneous data sets for improved decision-making. The authors present a first-of-its-kind comprehensive review of big data opportunities and challenges in the smart grid industry. This book provides succinct and useful theory, practical algorithms, and case studies to improve power grid operations and planning utilizing big data, making it a useful graduate-level reference for students, faculty, and practitioners on the future grid.

Dieser Sammelband verbindet theoretische Grundlagen und praktische Anwendungen von Künstlicher Intelligenz (KI) und Data Science: Anerkannte Experten stellen in ihren Beiträgen den aktuellen Stand in Forschung und Wirtschaft dar – und bieten so einen einzigartigen Überblick über aktuelle Konzepte und ihre Umsetzung in Unternehmen. Im ersten Teil des Buchs werden die Methoden und Algorithmen skizziert, die sich größtenteils aus einer Kombination von Statistik und Informatik ergeben und auf Verfahren des Maschinellen Lernens bis hin zu Deep Learning und KI basieren. Im zweiten Teil wird die konzeptionelle Umsetzung in der Praxis skizziert: Hier wird insbesondere aufgezeigt, welche Herausforderungen in der Praxis auftreten – ob nun bei der Einbettung der Daten-Use-Cases in eine Gesamtstrategie oder bei der Produktivsetzung, Weiterentwicklung und dem Betrieb von Daten-basierten Lösungen. Der dritte Teil zeigt das breite Potpourri von Data Science in der Praxis: Branchengrößenwie Allianz, ADAC, BMW, Deutsche Bahn, Lufthansa, REWE, RTL, St. Galler Stadtwerke, SwissRe und viele weitere zeigen konkret, welche Erfahrungen sie bei ihren Projekten gesammelt haben. Fachartikel von über 20 namhaften Unternehmen decken die spezifischen Anforderungen ihrer jeweiligen Branchen ab. Das Buch möchte die interdisziplinäre Diskussion und Kooperation zwischen Wissenschaft und Wirtschaft fördern und richtet sich daher an verschiedene Lesergruppen:Studierende und Absolventen, die Orientierung für die eigene Laufbahn suchen.Forschende und Lehrende, die einen Einblick in praxisrelevante Einsatzgebiete erhalten möchten.Anwender, Praktiker und Entscheider, die sich über Chancen und Herausforderungen von KI in der Praxis informieren möchten.

New to Oracle Global Data Services? You've come to the right place. This book will show you how to leverage the power of Oracle GDS to ensure runtime load balancing, region affinity, replication lag tolerance-based workload routing, and inter-database service failover. In particular, you will see how to maximize the utilization of replication investments with Oracle GDS. The book starts by guiding you through the installation and configuration of GDS and provides details for each component in the GDS framework. Next, you'll learn how to configure various components of Oracle GDS in standalone environments. Hands-on exercises that explore the advantages of GDS with different test cases utilizing Active Data Guard (ADG), Oracle GoldenGate (OGG), and Oracle Real Application Clusters (RAC) will help you put your learning in context. The book concludes with a demonstration of how to add Oracle GDS to OEM for monitoring and troubleshooting. You'll also see how to monitor Oracle GDS in a centralized location using Oracle Enterprise Manager Cloud Control. After completing this book, you will understand the architecture, components, and implementation strategies of GDS using ADG and OGG in mission-critical environments. What You Will Learn Understand Oracle Global Data Services architecture and its various componentsInstall and configure Oracle Global Data ServicesUse Global Data Services with Active Data Guard and Oracle Golden Gate.Monitor Global Data Services using Oracle Enterprise Manager Cloud Control.Troubleshoot issues in Global Data Services Who This Book Is For Oracle database administrators, Oracle database architects, Oracle technical managers, Oracle application business analysts, and Oracle data engineers.

This book constitutes selected papers from the 19th European, Mediterranean, and Middle Eastern Conference, EMCIS 2022, which was held virtually during December 7-8, 2022.EMCIS covers technical, organizational, business, and social issues in the application of information technology and is dedicated to the definition and establishment of Information Systems (IS) as a discipline of high impact for IS professionals and practitioners. It focuses on approaches that facilitate the identification of innovative research of significant relevance to the IS discipline following sound research methodologies that lead to results of measurable impact. The 47 papers presented in this volume were carefully reviewed and selected from a total of 136 submissions. They were organized in topical sections named: Artificial intelligence; big data and analytics; blockchain technology and applications; cloud computing; digital governance; digital services and social media; emerging computing technologies and trends for business process management; enterprise systems; information system security and information privacy protection; innovative research projects; IT governance and alignment; management and organizational issues in information systems; and metaverse.

Big Data technologies have the potential to revolutionize the agriculture sector, in particular food safety and quality practices. This book is designed to provide a foundational understanding of various applications of Big Data in Food Safety. Big Data requires the use of sophisticated approaches for cleaning, processing and extracting useful information to improve decision-making. The contributed volume reviews some of these approaches and algorithms in the context of real-world food safety studies. Food safety and quality related data are being generated in large volumes and from a variety of sources such as farms, processors, retailers, government organizations, and other industries. The editors have included examples of how big data can be used in the fields of bacteriology, virology and mycology to improve food safety. Additional chapters detail how the big data sources are aggregated and used in food safety and quality areas such as food spoilage and quality deterioration along the supply chain, food supply chain traceability, as well as policy and regulations. The volume also contains solutions to address standardization, data interoperability, and other data governance and data related technical challenges. Furthermore, this volume discusses how the application of machine-learning has successfully improved the speed and/or accuracy of many processes in the food supply chain, and also discusses some of the inherent challenges. Included in this volume as well is a practical example of the digital transformation that happened in Dubai, with a particular emphasis on how data is enabling better decision-making in food safety. To complete this volume, researchers discuss how although big data is and will continue to be a major disruptor in the area of food safety, it also raises some important questions with regards to issues such as security/privacy, data control and data governance, all of which must be carefully considered by governments and law makers.

This book constitutes the proceedings of the 26th International Conference on Enterprise Design, Operations, and Computing, EDOC 2022, which took place in Bozen-Bolzano, Italy, in October 2022. The 15 full papers included in this book were carefully reviewed and selected from 48 submissions. They were organized in topical sections as follows: enterprise security; enterprise architecture; business process modeling and monitoring; business process mining and discovery; and process-driven applications.

Von „Big Data“ über die „Künstliche Intelligenz“ bis hin zur „Sozialen Robotik“: Im Kontext der Digitalisierung gibt es unzählige Fachtermini. Das vorliegende Nachschlagewerk ist für alle geeignet, die einen schnellen Einstieg in das Gebiet der Digitalisierung suchen und sich für Fragen der Ethik interessieren. In 350 übersichtlichen Beiträgen werden die Grundlagen und Entwicklungen leicht verständlich erläutert.

This book explores the employment of market mechanisms for data-interactive innovations. Based on the concept of innovators'marketplaces the book introduces a new concept of'data jackets'to enable analysis of what kind of data exist, where they are located, and what kind of information they hold, even if the contents of data cannot be made publicly available.The book presents the concept of a marketplace for data in the case of data-interactive innovations. It introduces the marketplace as a platform for value-based exchange of data and - based on the idea of the innovators'marketplace - explains how data jackets can be utilized independently from the actual contents of the data. Specific chapters deepen the understanding of variables, constraints and intentions as constituent parts of data jackets, and the extension to variable quest, a process towards the design of data. A number of case studies showcases how the methods and processes presented can be employed in real-life contexts. Finally the authors present some extensions of the concept for web-based IMDJ and connections to business information system and an outlook.

Wineinformatics is a new data science application with a focus on understanding wine through artificial intelligence. Thousands of new wine reviews are produced monthly, which benefits the understanding of wine through wine experts for winemakers and consumers. This book systematically investigates how to process human language format reviews and mine useful knowledge from a large volume of processed data. This book presents a human language processing tool named Computational Wine Wheel to process professional wine reviews and three novel Wineinformatics studies to analyze wine quality, price and reviewers. Through the lens of data science, the author demonstrates how the wine receives 90+ scores out of 100 points from Wine Spectator, how to predict a wine's specific grade and price through wine reviews and how to rank a group of wine reviewers. The book also shows the advanced application of the Computational Wine Wheel to capture more information hidden in wine reviews and the possibility of extending the wheel to coffee, tea beer, sake and liquors. This book targets computer scientists, data scientists and wine industrial researchers, who are interested in Wineinformatics. Senior data science undergraduate and graduate students may also benefit from this book.

This book examines recent developments in Operations Management, and focuses on four major application areas: dynamic pricing, assortment optimization, supply chain and inventory management, and healthcare operations. Data-driven optimization in which real-time input of data is being used to simultaneously learn the (true) underlying model of a system and optimize its performance, is becoming increasingly important in the last few years, especially with the rise of Big Data.

This book contains extended, revised and selected papers from the 23rd International Conference on Enterprise Information Systems, ICEIS 2021, held online during April 2021. The 26 papers presented in this volume were carefully reviewed and selected for inclusion from a total of 241 submissions. They are grouped in sections on databases and information systems integration, artificial intelligence and decision support systems, information systems analysis and specification, software agents and internet computing, human-computer interaction, and enterprise architecture.

Gegenwärtig gibt es einen starken Hype um die Themen künstliche Intelligenz, Machine Learning und Data Science. Doch wie lassen sich datengetriebene Methoden und Technologien nutzen und in Unternehmen gewinnbringend einsetzen? Dieses Buch zeigt praxisnah und anschaulich, wie mit der richtigen Datenbasis und Datenmodellen der Wert von Daten für Unternehmen erschlossen werden kann. Dabei geht es nicht um technische Details zu Algorithmen und Technologien, sondern um Instrumente und sofort anwendbare Lösungen zur erfolgreichen Projektumsetzung.Jedes Kapitel stellt die jeweilige Zielsetzung vor, vermittelt anschließend alle Inhalte und fasst am Ende – neben einer Checkliste der wichtigsten Maßnahmen – die Aussagen für verschiedene Organisationsformen zusammen. Anhand zahlreicher Beispiele wird gezeigt, wie Struktur und Vorgehen den Anforderungen der komplexen Werkzeuge gerecht werden können.

This book provides a review of advanced topics relating to the theory, research, analysis and implementation in the context of big data platforms and their applications, with a focus on methods, techniques, and performance evaluation. The explosive growth in the volume, speed, and variety of data being produced every day requires a continuous increase in the processing speeds of servers and of entire network infrastructures, as well as new resource management models. This poses significant challenges (and provides striking development opportunities) for data intensive and high-performance computing, i.e., how to efficiently turn extremely large datasets into valuable information and meaningful knowledge.The task of context data management is further complicated by the variety of sources such data derives from, resulting in different data formats, with varying storage, transformation, delivery, and archiving requirements. At the same time rapid responses are neededfor real-time applications. With the emergence of cloud infrastructures, achieving highly scalable data management in such contexts is a critical problem, as the overall application performance is highly dependent on the properties of the data management service.

This book gathers the best papers presented at the second conference held by the Russian chapter of the Association for Information Systems (AIS), which took place in Yekaterinburg, Russian Federation, in December 2019. It shares the latest insights into various aspects of the digitalization of the economy and the consequences of transformation in public administration, business and public life. Integrating a broad range of analytical perspectives, including economic, social and technological, this interdisciplinary book is particularly relevant for scientists, digital technology users, companies and public institutions.