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000891497 019__ $$a1106158537
000891497 020__ $$a9783030118211$$q(electronic book)
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000891497 08204 $$a005.7$$223
000891497 24500 $$aApplied data science :$$blessons learned for the data driven business /$$cMartin Braschler, Thilo Stadelmann, Kurt Stockinger, editors
000891497 264_1 $$aBasel :$$bSpringer,$$c[2019]
000891497 264_4 $$c©2019
000891497 300__ $$a1 online resource (xiii, 465 pages) :$$billustrations
000891497 336__ $$atext$$btxt$$2rdacontent
000891497 337__ $$acomputer$$bc$$2rdamedia
000891497 338__ $$aonline resource$$bcr$$2rdacarrier
000891497 504__ $$aIncludes bibliographical references.
000891497 50500 $$tFoundations --$$tIntroduction to Applied Data Science /$$rThilo Stadelmann, Martin Braschler, Kurt Stockinger --$$tData Science /$$rMartin Braschler, Thilo Stadelmann, Kurt Stockinger --$$tData Scientists /$$rThilo Stadelmann, Kurt Stockinger, Gundula Heinatz Bürki, Martin Braschler --$$tData Products /$$rJürg Meierhofer, Thilo Stadelmann, Mark Cieliebak --$$tLegal Aspects of Applied Data Science /$$rMichael Widmer, Stefan Hegy --$$tRisks and Side Effects of Data Science and Data Technology /$$rClemens H. Cap --$$tUse Cases --$$tOrganization /$$rMartin Braschler, Thilo Stadelmann, Kurt Stockinger --$$tWhat Is Data Science? --$$tMichael L. Brodie --$$tOn Developing Data Science /$$rMichael L. Brodie --$$tThe Ethics of Big Data Applications in the Consumer Sector /$$rMarkus Christen, Helene Blumer, Christian Hauser, Markus Huppenbauer --$$tStatistical Modelling /$$rMarcel Dettling, Andreas Ruckstuhl --$$tBeyond ImageNet: Deep Learning in Industrial Practice /$$rThilo Stadelmann, Vasily Tolkachev, Beate Sick, Jan Stampfli, Oliver Dürr --$$tThe Beauty of Small Data: An Information Retrieval Perspective /$$rMartin Braschler --$$tNarrative Visualization of Open Data /$$rPhilipp Ackermann, Kurt Stockinger --$$tSecurity of Data Science and Data Science for Security /$$rBernhard Tellenbach, Marc Rennhard, Remo Schweizer --$$tOnline Anomaly Detection over Big Data Streams /$$rLaura Rettig, Mourad Khayati, Philippe Cudré-Mauroux, Michał Piorkówski --$$tUnsupervised Learning and Simulation for Complexity Management in Business Operations /$$rLukas Hollenstein, Lukas Lichtensteiger, Thilo Stadelmann, Mohammadreza Amirian, Lukas Budde, Jürg Meierhofer et al. --$$tData Warehousing and Exploratory Analysis for Market Monitoring /$$rMelanie Geiger, Kurt Stockinger --$$tMining Person-Centric Datasets for Insight, Prediction, and Public Health Planning /$$rJonathan P. Leidig, Greg Wolffe --$$tEconomic Measures of Forecast Accuracy for Demand Planning: A Case-Based Discussion /$$rThomas Ott, Stefan Glüge, Richard Bödi, Peter Kauf --$$tLarge-Scale Data-Driven Financial Risk Assessment /$$rWolfgang Breymann, Nils Bundi, Jonas Heitz, Johannes Micheler, Kurt Stockinger --$$tGovernance and IT Architecture /$$rSerge Bignens, Murat Sariyar, Ernst Hafen --$$tImage Analysis at Scale for Finding the Links Between Structure and Biology /$$rKevin Mader --$$tLessons Learned and Outlook --$$tLessons Learned from Challenging Data Science Case Studies /$$rKurt Stockinger, Martin Braschler, Thilo Stadelmann.
000891497 506__ $$aAccess limited to authorized users.
000891497 520__ $$a"This book has two main goals: to define data science through the work of data scientists and their results, namely data products, while simultaneously providing the reader with relevant lessons learned from applied data science projects at the intersection of academia and industry. As such, it is not a replacement for a classical textbook (i.e., it does not elaborate on fundamentals of methods and principles described elsewhere), but systematically highlights the connection between theory, on the one hand, and its application in specific use cases, on the other. With these goals in mind, the book is divided into three parts: Part I pays tribute to the interdisciplinary nature of data science and provides a common understanding of data science terminology for readers with different backgrounds. These six chapters are geared towards drawing a consistent picture of data science and were predominantly written by the editors themselves. Part II then broadens the spectrum by presenting views and insights from diverse authors - some from academia and some from industry, ranging from financial to health and from manufacturing to e-commerce. Each of these chapters describes a fundamental principle, method or tool in data science by analyzing specific use cases and drawing concrete conclusions from them. The case studies presented, and the methods and tools applied, represent the nuts and bolts of data science. Finally, Part III was again written from the perspective of the editors and summarizes the lessons learned that have been distilled from the case studies in Part II. The section can be viewed as a meta-study on data science across a broad range of domains, viewpoints and fields. Moreover, it provides answers to the question of what the mission-critical factors for success in different data science undertakings are. The book targets professionals as well as students of data science: first, practicing data scientists in industry and academia who want to broaden their scope and expand their knowledge by drawing on the authors' combined experience. Second, decision makers in businesses who face the challenge of creating or implementing a data-driven strategy and who want to learn from success stories spanning a range of industries. Third, students of data science who want to understand both the theoretical and practical aspects of data science, vetted by real-world case studies at the intersection of academia and industry."--Publisher's website.
000891497 650_0 $$aBig data.
000891497 650_0 $$aElectronic data processing.
000891497 7001_ $$aBraschler, Martin,$$eeditor.
000891497 7001_ $$aStadelmann, Thilo,$$eeditor.
000891497 7001_ $$aStockinger, Kurt,$$eeditor.
000891497 852__ $$bebk
000891497 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-030-11821-1$$zOnline Access$$91397441.1
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000891497 980__ $$aEBOOK
000891497 980__ $$aBIB
000891497 982__ $$aEbook
000891497 983__ $$aOnline
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