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Handbook of Data Quality
The issue of data quality is as old as data itself. However, the proliferation of diverse, large-scale and often publically available data on the Web has increased the risk of poor data quality and misleading data interpretations. On the other hand, data is now exposed at a much more strategic level e.g. through business intelligence systems, increasing manifold the stakes involved for individuals, corporations as well as government agencies. There, the lack of knowledge about data accuracy, currency or completeness can have erroneous and even catastrophic results. With these changes, traditional approaches to data management in general, and data quality control specifically, are challenged....
Challenges Between Competition and Collaboration
European manufacturing industries are changing fast. Amid the pressures of globalisation, emerging markets and shifting geographical patterns of consumption and production, competition and collaboration need to be redefined. The book contains roadmaps for survival in the emerging global competitive arena by and for practitioners, as well as concrete examples and theoretical studies across industries. New forms of cooperation are analysed which combine intensive collaboration with high competition in networks of excellence among suppliers, manufacturers and customers. The success factors for such industrial networks are described in detail, as well as their benefits and potential risks. In a multidisciplinary approach, the book draws on parallels from other fields and disciplines in order to explore the many facets of competition and collaboration.
The Next Wave of Sociotechnical Design
This book constitutes the thoroughly refereed proceedings of the 16th International Conference on Design Science Research in Information Systems and Technology, DESRIST 2021, held in Kristiansand, Norway, in August 2021.* The 24 revised full research papers, included in the volume together with 6 short contributions and 7 prototype papers, were carefully reviewed and selected from 78 submissions. They are organized in the following topical sections: impactful sociotechnical design; problem and contribution articulation; design knowledge for reuse; emerging methods and frameworks for DSR; DSR and governance; the new boundaries of DSR. *Apart from the planned on-site event, the hybrid conference model was explored due to the Covid-19 pandemic.
Deliver Value in the Data Economy
The book is for data monetization purposes, helps you to build bridge between IT department and business design to maximise data driven value creation. Data productizement and servitization are explained with real-world example case stories. This book is primarily for data business developers and contains just bare minimum of technical terms.
Foundations of Data Quality Management
Data quality is one of the most important problems in data management. A database system typically aims to support the creation, maintenance, and use of large amount of data, focusing on the quantity of data. However, real-life data are often dirty: inconsistent, duplicated, inaccurate, incomplete, or stale. Dirty data in a database routinely generate misleading or biased analytical results and decisions, and lead to loss of revenues, credibility and customers. With this comes the need for data quality management. In contrast to traditional data management tasks, data quality management enables the detection and correction of errors in the data, syntactic or semantic, in order to improve the...
Data Governance and Data Management
This book delves into the concept of data as a critical enterprise asset needed for informed decision making, compliance, regulatory reporting and insights into trends, behaviors, performance and patterns. With good data being key to staying ahead in a competitive market, enterprises capture and store exponential volumes of data. Considering the business impact of data, there needs to be adequate management around it to derive the best value. Data governance is one of the core data management related functions. However, it is often overlooked, misunderstood or confused with other terminologies and data management functions. Given the pervasiveness of data and the importance of data, this boo...
Global Perspectives on Design Science Research
This book constitutes the refereed proceedings of the 5th International Conference on Global Perspectives on Design Science Research, DERIST 2010, held in St. Gallen, Switzerland, in June 2010. The 35 revised full papers presented together with 10 revised short papers were carefully reviewed and selected from 80 submissions. The papers are organized in topical sections on organising design research, reflecting design science research, design research techniques, design and context, design and organisation, design and information, design research exemplars, design and behaviour, designing collaboration, as well as design and requirements engineering.
Industrial Applications of Holonic and Multi-Agent Systems
This book constitutes the refereed proceedings of the 8th International Conference on Industrial Applications of Holonic and Multi-Agent Systems, HoloMAS 2017, held in Lyon, France, in August 2017. The 19 revised full papers presented were carefully reviewed and selected from 27 submissions. The papers are organized in the following topical sections: scheduling; knowledge engineering; modeling, simulation and reconfiguration; energy systems;and MAS in various areas.
Supporting Operational and Real-time Planning Tasks of Road Freight Transport with Machine Learning. Guiding the Implementation of Machine Learning Algorithms
World-wide trends such as globalization, demographic shifts, increased customer demands, and shorter product lifecycles present a significant challenge to the road freight transport industry: meeting the growing road freight transport demand economically while striving for sustainability. Artificial intelligence, particularly machine learning, is expected to empower transport planners to incorporate more information and react quicker to the fast-changing decision environment. Hence, using machine learning can lead to more efficient and effective transport planning. However, despite the promising prospects of machine learning in road freight transport planning, both academia and industry struggle to identify and implement suitable use cases to gain a competitive edge. In her dissertation, Sandra Lechtenberg explores how machine learning can enhance decision-making in operational and real-time road freight transport planning. She outlines an implementation guideline, which involves identifying decision tasks in planning processes, assessing their suitability for machine learning, and proposing steps to follow when implementing respective algorithms.
Innovation Through Information Systems
This book presents the current state of research in information systems and digital transformation. Due to the global trend of digitalization and the impact of the Covid 19 pandemic, the need for innovative, high-quality research on information systems is higher than ever. In this context, the book covers a wide range of topics, such as digital innovation, business analytics, artificial intelligence, and IT strategy, which affect companies, individuals, and societies. This volume gathers the revised and peer-reviewed papers on the topic "Management" presented at the International Conference on Information Systems, held at the University of Duisburg-Essen in 2021.
