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Author: Andreas Wierse Publisher: Walter de Gruyter GmbH & Co KG ISBN: 3110461919 Category : Technology & Engineering Languages : de Pages : 440
Book Description
Wenn in Datenbergen wertvolle Geheimnisse schlummern, aus denen Profit erzielt werden soll, dann geht es um Big Data. Doch wie schöpft man aus »großen Daten« echte Werte, wenn man nicht gerade Google ist? Um aus Unternehmens-, Maschinen- oder Sensordaten einen Ertrag zu erzielen, reicht Big Data-Technologie allein nicht aus. Entscheidend sind die übergeordneten Innovations prozesse: die smarte Analyse von Big Data. Erst durch den kompetenten Einsatz der richtigen Werkzeuge und Techniken werden aus Big Data tatsächlich Smart Data. Das Praxishandbuch Smart Data Analytics gibt einen Überblick über die Technologie, die bei der Analyse von großen und heterogenen Datenmengen – inklusive Echtzeitdaten – zum Einsatz kommt. Elf Praxisbeispiele zeigen die konkrete Anwendung in kleinen und mittelständischen Unternehmen. So erfahren Sie, wie Sie Ihr Smart Data Analytics-Projekt in Ihrem eigenen Unternehmen vorbereiten und umsetzen können. Das Buch erläutert neben den organisatorischen Aspekten auch die rechtlichen Rahmenbedingungen. Und es zeigt, wie Sie sowohl den Nutzen bewerten können, der aus den Daten gezogen werden soll, als auch den Aufwand, den Sie dafür betreiben müssen. Denn Smart Data steht für mehr als nur die Untersuchung großer Datenmengen: Smart Data Analytics ist der Schlüssel zu einem smarten Umgang mit Ihren Unternehmensdaten und hilft, bislang unentdecktes Potenzial zu entdecken. Dr. Andreas Wierse studierte Mathematik und promovierte in den Ingenieurwissenschaften im Bereich Visualisierung, seit 2011 unterstützt er mittelständische Unternehmen rund um Big und Smart Data Technologie. Dr. Till Riedel lehrt als Informatiker am KIT und koordiniert im Smart Data Solution Center Baden-Württemberg und Smart Data Innovation Lab Forschung und Innovation auf industriellen Datenschätzen.
Author: Andreas Wierse Publisher: Walter de Gruyter GmbH & Co KG ISBN: 3110461919 Category : Technology & Engineering Languages : de Pages : 440
Book Description
Wenn in Datenbergen wertvolle Geheimnisse schlummern, aus denen Profit erzielt werden soll, dann geht es um Big Data. Doch wie schöpft man aus »großen Daten« echte Werte, wenn man nicht gerade Google ist? Um aus Unternehmens-, Maschinen- oder Sensordaten einen Ertrag zu erzielen, reicht Big Data-Technologie allein nicht aus. Entscheidend sind die übergeordneten Innovations prozesse: die smarte Analyse von Big Data. Erst durch den kompetenten Einsatz der richtigen Werkzeuge und Techniken werden aus Big Data tatsächlich Smart Data. Das Praxishandbuch Smart Data Analytics gibt einen Überblick über die Technologie, die bei der Analyse von großen und heterogenen Datenmengen – inklusive Echtzeitdaten – zum Einsatz kommt. Elf Praxisbeispiele zeigen die konkrete Anwendung in kleinen und mittelständischen Unternehmen. So erfahren Sie, wie Sie Ihr Smart Data Analytics-Projekt in Ihrem eigenen Unternehmen vorbereiten und umsetzen können. Das Buch erläutert neben den organisatorischen Aspekten auch die rechtlichen Rahmenbedingungen. Und es zeigt, wie Sie sowohl den Nutzen bewerten können, der aus den Daten gezogen werden soll, als auch den Aufwand, den Sie dafür betreiben müssen. Denn Smart Data steht für mehr als nur die Untersuchung großer Datenmengen: Smart Data Analytics ist der Schlüssel zu einem smarten Umgang mit Ihren Unternehmensdaten und hilft, bislang unentdecktes Potenzial zu entdecken. Dr. Andreas Wierse studierte Mathematik und promovierte in den Ingenieurwissenschaften im Bereich Visualisierung, seit 2011 unterstützt er mittelständische Unternehmen rund um Big und Smart Data Technologie. Dr. Till Riedel lehrt als Informatiker am KIT und koordiniert im Smart Data Solution Center Baden-Württemberg und Smart Data Innovation Lab Forschung und Innovation auf industriellen Datenschätzen.
Author: Andreas Wierse Publisher: Walter de Gruyter GmbH & Co KG ISBN: 3110463954 Category : Technology & Engineering Languages : de Pages : 440
Book Description
Wenn in Datenbergen wertvolle Geheimnisse schlummern, aus denen Profit erzielt werden soll, dann geht es um Big Data. Doch wie schöpft man aus »großen Daten« echte Werte, wenn man nicht gerade Google ist? Um aus Unternehmens-, Maschinen- oder Sensordaten einen Ertrag zu erzielen, reicht Big Data-Technologie allein nicht aus. Entscheidend sind die übergeordneten Innovations prozesse: die smarte Analyse von Big Data. Erst durch den kompetenten Einsatz der richtigen Werkzeuge und Techniken werden aus Big Data tatsächlich Smart Data. Das Praxishandbuch Smart Data Analytics gibt einen Überblick über die Technologie, die bei der Analyse von großen und heterogenen Datenmengen – inklusive Echtzeitdaten – zum Einsatz kommt. Elf Praxisbeispiele zeigen die konkrete Anwendung in kleinen und mittelständischen Unternehmen. So erfahren Sie, wie Sie Ihr Smart Data Analytics-Projekt in Ihrem eigenen Unternehmen vorbereiten und umsetzen können. Das Buch erläutert neben den organisatorischen Aspekten auch die rechtlichen Rahmenbedingungen. Und es zeigt, wie Sie sowohl den Nutzen bewerten können, der aus den Daten gezogen werden soll, als auch den Aufwand, den Sie dafür betreiben müssen. Denn Smart Data steht für mehr als nur die Untersuchung großer Datenmengen: Smart Data Analytics ist der Schlüssel zu einem smarten Umgang mit Ihren Unternehmensdaten und hilft, bislang unentdecktes Potenzial zu entdecken. Dr. Andreas Wierse studierte Mathematik und promovierte in den Ingenieurwissenschaften im Bereich Visualisierung, seit 2011 unterstützt er mittelständische Unternehmen rund um Big und Smart Data Technologie. Dr. Till Riedel lehrt als Informatiker am KIT und koordiniert im Smart Data Solution Center Baden-Württemberg und Smart Data Innovation Lab Forschung und Innovation auf industriellen Datenschätzen.
Author: Julia Ertel Publisher: GRIN Verlag ISBN: 3346640639 Category : Business & Economics Languages : en Pages : 145
Book Description
Bachelor Thesis from the year 2021 in the subject Business economics - Miscellaneous, grade: 1,0, Pforzheim University, language: English, abstract: Big data is getting larger, the pressure in the market to use the existing data is getting stronger and therefore also the number of companies that address the topic of data science increases. This dissertation focuses on identifying big or smart data science trends in marketing and sales within the consumer-packaged goods industry. The objective of this research is to address actual opportunities around data science for the selected focus area. The following research project analyzes those opportunities and identifies nine data science trends. Via in-depth interviews, the expert’s experiences and difficulties with data science are questioned, emotions that arise through the interaction with this science are recognized, and potentials for improvements are discussed. Subsequently, central meaningful quotations are analyzed with Mayring’s qualitative content analysis, reformulated into condensed codes, and summarized through eighteen overarching categories. The general findings of this analysis include the necessity of smart data insights within this low margin industry, the dependence on consultancy support due to knowledge gaps, expandable engagement in the B2B environment, the promotion of data-thinking and acting, the merge of sales and marketing for data science knowledge generations, and the extension of data science knowledge to maintain competitive advantage within the market for the long run. The improvement proposals consist mainly of automated data cleaning, intelligent algorithms, data handling knowledge development, data democracy, and knowledge combinations in form of project dependent focus teams to broaden data science applications within the industry.
Author: Devendra Kumar Sharma Publisher: Springer Nature ISBN: 3031460928 Category : Computers Languages : en Pages : 466
Book Description
This book introduces big data analytics and corresponding applications in smart grids. The characterizations of big data, smart grids as well as a huge amount of data collection are first discussed as a prelude to illustrating the motivation and potential advantages of implementing advanced data analytics in smart grids. Basic concepts and the procedures of typical data analytics for general problems are also discussed. The advanced applications of different data analytics in smart grids are addressed as the main part of this book. By dealing with a huge amount of data from electricity networks, meteorological information system, geographical information system, etc., many benefits can be brought to the existing power system and improve customer service as well as social welfare in the era of big data. However, to advance the applications of big data analytics in real smart grids, many issues such as techniques, awareness, and synergies have to be overcome. This book provides deployment of semantic technologies in data analysis along with the latest applications across the field such as smart grids.
Author: Chun Sing Lai Publisher: Springer Nature ISBN: 3030521559 Category : Technology & Engineering Languages : en Pages : 403
Book Description
This book provides a comprehensive introduction to different elements of smart city infrastructure - smart energy, smart water, smart health, and smart transportation - and how they work independently and together. Theoretical development and practical applications are presented, along with related standards, recommended practices, and professional guidelines. Throughout the book, diagrams and case studies are provided that demonstrate the systems presented, and extensive use of scenarios helps readers better grasp how smart grids, the Internet of Things, big data analytics, and trading models can improve road safety, healthcare, smart water management, and a low-carbon economy. A must-read for practicing engineers, consultants, regulators, utility operators, and environmentalists involved in smart city development, the book will also appeal to city planners and designers, as well as upper-level undergraduate and graduate students studying energy, environmental science, technology, economics, signal processing, information science, and power engineering.
Author: Simon Elias Bibri Publisher: Springer ISBN: 3030173127 Category : Political Science Languages : en Pages : 337
Book Description
We are living at the dawn of what has been termed ‘the fourth paradigm of science,’ a scientific revolution that is marked by both the emergence of big data science and analytics, and by the increasing adoption of the underlying technologies in scientific and scholarly research practices. Everything about science development or knowledge production is fundamentally changing thanks to the ever-increasing deluge of data. This is the primary fuel of the new age, which powerful computational processes or analytics algorithms are using to generate valuable knowledge for enhanced decision-making, and deep insights pertaining to a wide variety of practical uses and applications. This book addresses the complex interplay of the scientific, technological, and social dimensions of the city, and what it entails in terms of the systemic implications for smart sustainable urbanism. In concrete terms, it explores the interdisciplinary and transdisciplinary field of smart sustainable urbanism and the unprecedented paradigmatic shifts and practical advances it is undergoing in light of big data science and analytics. This new era of science and technology embodies an unprecedentedly transformative and constitutive power—manifested not only in the form of revolutionizing science and transforming knowledge, but also in advancing social practices, producing new discourses, catalyzing major shifts, and fostering societal transitions. Of particular relevance, it is instigating a massive change in the way both smart cities and sustainable cities are studied and understood, and in how they are planned, designed, operated, managed, and governed in the face of urbanization. This relates to what has been dubbed data-driven smart sustainable urbanism, an emerging approach based on a computational understanding of city systems and processes that reduces urban life to logical and algorithmic rules and procedures, while also harnessing urban big data to provide a more holistic and integrated view or synoptic intelligence of the city. This is increasingly being directed towards improving, advancing, and maintaining the contribution of both sustainable cities and smart cities to the goals of sustainable development. This timely and multifaceted book is aimed at a broad readership. As such, it will appeal to urban scientists, data scientists, urbanists, planners, engineers, designers, policymakers, philosophers of science, and futurists, as well as all readers interested in an overview of the pivotal role of big data science and analytics in advancing every academic discipline and social practice concerned with data–intensive science and its application, particularly in relation to sustainability.
Author: Kuan-Ching Li Publisher: CRC Press ISBN: 0429018037 Category : Business & Economics Languages : en Pages : 410
Book Description
Smart Data: State-of-the-Art Perspectives in Computing and Applications explores smart data computing techniques to provide intelligent decision making and prediction services support for business, science, and engineering. It also examines the latest research trends in fields related to smart data computing and applications, including new computing theories, data mining and machine learning techniques. The book features contributions from leading experts and covers cutting-edge topics such as smart data and cloud computing, AI for networking, smart data deep learning, Big Data capture and representation, AI for Big Data applications, and more. Features Presents state-of-the-art research in big data and smart computing Provides a broad coverage of topics in data science and machine learning Combines computing methods with domain knowledge and a focus on applications in science, engineering, and business Covers data security and privacy, including AI techniques Includes contributions from leading researchers
Author: Kolla Bhanu Prakash Publisher: CRC Press ISBN: 1000413365 Category : Technology & Engineering Languages : en Pages : 297
Book Description
Big Data Analytics and Intelligent Techniques for Smart Cities covers fundamentals, advanced concepts, and applications of big data analytics for smart cities in a single volume. This comprehensive reference text discusses big data theory modeling and simulation for smart cities and examines case studies in a single volume. The text discusses how to develop a smart city and state-of-the-art system design, system verification, real-time control and adaptation, Internet of Things, and testbeds. It covers applications of smart cities as they relate to smart transportation/connected vehicle (CV) and intelligent transportation systems (ITS) for improved mobility, safety, and environmental protection. It will be useful as a reference text for graduate students in different areas including electrical engineering, computer science engineering, civil engineering, and electronics and communications engineering. Features: Technologies and algorithms associated with the application of big data for smart cities Discussions on big data theory modeling and simulation for smart cities Applications of smart cities as they relate to smart transportation and intelligent transportation systems (ITS) Discussions on concepts including smart education, smart culture, and smart transformation management for social and societal changes
Author: Tausifa Jan Saleem Publisher: John Wiley & Sons ISBN: 1119740770 Category : Mathematics Languages : en Pages : 402
Book Description
BIG DATA ANALYTICS FOR INTERNET OF THINGS Discover the latest developments in IoT Big Data with a new resource from established and emerging leaders in the field Big Data Analytics for Internet of Things delivers a comprehensive overview of all aspects of big data analytics in Internet of Things (IoT) systems. The book includes discussions of the enabling technologies of IoT data analytics, types of IoT data analytics, challenges in IoT data analytics, demand for IoT data analytics, computing platforms, analytical tools, privacy, and security. The distinguished editors have included resources that address key techniques in the analysis of IoT data. The book demonstrates how to select the appropriate techniques to unearth valuable insights from IoT data and offers novel designs for IoT systems. With an abiding focus on practical strategies with concrete applications for data analysts and IoT professionals, Big Data Analytics for Internet of Things also offers readers: A thorough introduction to the Internet of Things, including IoT architectures, enabling technologies, and applications An exploration of the intersection between the Internet of Things and Big Data, including IoT as a source of Big Data, the unique characteristics of IoT data, etc. A discussion of the IoT data analytics, including the data analytical requirements of IoT data and the types of IoT analytics, including predictive, descriptive, and prescriptive analytics A treatment of machine learning techniques for IoT data analytics Perfect for professionals, industry practitioners, and researchers engaged in big data analytics related to IoT systems, Big Data Analytics for Internet of Things will also earn a place in the libraries of IoT designers and manufacturers interested in facilitating the efficient implementation of data analytics strategies.
Author: Andreas Wierse
Author: Andreas Wierse
Author: Andreas Wierse
Author: Andreas Wierse
Author: Julia Ertel
Author: Devendra Kumar Sharma
Author: Chun Sing Lai
Author: Simon Elias Bibri
Author: Kuan-Ching Li
Author: Kolla Bhanu Prakash
Author: Tausifa Jan Saleem