Prof. Dr. Martin Braschler is a senior lecturer at the Zurich University of Applied Sciences (ZHAW), as well as head of the Information Engineering group that is located at the Institute of Applied Information Technology. His main research interests are in the field of unstructured information, specifically information retrieval evaluation, cross-language information retrieval, and natural language processing. He was one of the original initiators of the CLEF campaigns, which are the largest European forum for benchmarking of systems from the area of information retrieval and related fields. Prior to joining ZHAW, he served as head of research and innovation at Eurospider Information Technology AG, Zurich, Switzerland, a vendor of information retrieval solutions, and has thus extensive experience in the transfer of state-of-the-art technology to the commercial marketplace. Prof. Dr. Thilo Stadelmann is a senior lecturer in computer science at ZHAW School of Engineering in Winterthur. His current research focuses on applications of machine learning, especially deep learning, to diverse kinds of data. He is head of the ZHAW Data Science Laboratory and member of the board of the Swiss Alliance for Data-Intensive Services. Before joining ZHAW, Thilo headed a team of software developers and data miners at TWT GmbH Science & Innovation, developing tailor-made data management applications for the German automotive industry. He has more than 10 years of experience as a professional software developer. Prof. Dr. Kurt Stockinger is a senior lecturer in computer science at ZHAW and Director of Studies in Data Science. His research focuses on data warehousing (DWH), business intelligence (BI) and Big Data. He is also on the Advisory Board of Callista Group AG. Before joining ZHAW, Kurt was a DWH and BI Architect at Credit Suisse, Zurich where he worked on designing and implementing algorithmsfor a terabyte-scale enterprise data warehouse, data security, and DWH/BI applications. Prior, Kurt worked for four years at Lawrence Berkeley National Laboratory performing research on multi-dimensional indexing and query methods for large-scale scientific data as well as high-performance visual analytics. From 2000 to 2003 Kurt was heading the Replica Optimization Team of the EU Data Grid Project at CERN. In 2001 Kurt was a visiting researcher at California Institute of Technology.

• Preface.- 1 Introduction.- 2 Data Science.- 3 Data Scientists.- 4 Data products.- 5 Legal Aspects of Applied Data Science.- 6 Risks and Side Effects of Data Science and Data Technology.- 7 Organization.- 8 What is Data Science?.- 9 On Developing Data Science.- 10 The ethics of Big Data applications in the consumer sector.- 11 Statistical Modelling.- 12 Beyond ImageNet - Deep Learning in Industrial Practice.- 13 THE BEAUTY OF SMALL DATA - AN INFORMATION RETRIEVAL PERSPECTIVE.- 14 Narrative Visualization of Open Data.- 15 Security of Data Science and Data Science for Security.- 16 Online Anomaly Detection over Big Data Streams.- 17 Unsupervised Learning and Simulation for Complexity Management in Business Operations.- 18 Data Warehousing and Exploratory Analysis for Market Monitoring.- 19 Mining Person-Centric Datasets for Insight, Prediction, and Public Health Planning.- 20 Economic Measures of Forecast Accuracy for Demand Planning - A Case-Based Discussion.- 21 Large-Scale Data-DrivenFinancial Risk Assessment.- 22 Governance and IT Architecture.- 23 Image Analysis at Scale for Finding the Links between Structure and Biology.- 24 Lessons Learned from Challenging Data Science Case Studies.

Prof. Dr. Martin Braschler is a senior lecturer at the Zurich University of Applied Sciences (ZHAW), as well as head of the Information Engineering group that is located at the Institute of Applied Information Technology. His main research interests are in the field of unstructured information, specifically information retrieval evaluation, cross-language information retrieval, and natural language processing. He was one of the original initiators of the CLEF campaigns, which are the largest European forum for benchmarking of systems from the area of information retrieval and related fields. Prior to joining ZHAW, he served as head of research and innovation at Eurospider Information Technology AG, Zurich, Switzerland, a vendor of information retrieval solutions, and has thus extensive experience in the transfer of state-of-the-art technology to the commercial marketplace. Prof. Dr. Thilo Stadelmann is a senior lecturer in computer science at ZHAW School of Engineering in Winterthur. His current research focuses on applications of machine learning, especially deep learning, to diverse kinds of data. He is head of the ZHAW Data Science Laboratory and member of the board of the Swiss Alliance for Data-Intensive Services. Before joining ZHAW, Thilo headed a team of software developers and data miners at TWT GmbH Science & Innovation, developing tailor-made data management applications for the German automotive industry. He has more than 10 years of experience as a professional software developer. Prof. Dr. Kurt Stockinger is a senior lecturer in computer science at ZHAW and Director of Studies in Data Science. His research focuses on data warehousing (DWH), business intelligence (BI) and Big Data. He is also on the Advisory Board of Callista Group AG. Before joining ZHAW, Kurt was a DWH and BI Architect at Credit Suisse, Zurich where he worked on designing and implementing algorithmsfor a terabyte-scale enterprise data warehouse, data security, and DWH/BI applications. Prior, Kurt worked for four years at Lawrence Berkeley National Laboratory performing research on multi-dimensional indexing and query methods for large-scale scientific data as well as high-performance visual analytics. From 2000 to 2003 Kurt was heading the Replica Optimization Team of the EU Data Grid Project at CERN. In 2001 Kurt was a visiting researcher at California Institute of Technology.

• Preface.- 1 Introduction.- 2 Data Science.- 3 Data Scientists.- 4 Data products.- 5 Legal Aspects of Applied Data Science.- 6 Risks and Side Effects of Data Science and Data Technology.- 7 Organization.- 8 What is Data Science?.- 9 On Developing Data Science.- 10 The ethics of Big Data applications in the consumer sector.- 11 Statistical Modelling.- 12 Beyond ImageNet - Deep Learning in Industrial Practice.- 13 THE BEAUTY OF SMALL DATA - AN INFORMATION RETRIEVAL PERSPECTIVE.- 14 Narrative Visualization of Open Data.- 15 Security of Data Science and Data Science for Security.- 16 Online Anomaly Detection over Big Data Streams.- 17 Unsupervised Learning and Simulation for Complexity Management in Business Operations.- 18 Data Warehousing and Exploratory Analysis for Market Monitoring.- 19 Mining Person-Centric Datasets for Insight, Prediction, and Public Health Planning.- 20 Economic Measures of Forecast Accuracy for Demand Planning - A Case-Based Discussion.- 21 Large-Scale Data-DrivenFinancial Risk Assessment.- 22 Governance and IT Architecture.- 23 Image Analysis at Scale for Finding the Links between Structure and Biology.- 24 Lessons Learned from Challenging Data Science Case Studies.

Prof. Dr. Martin Braschler is a senior lecturer at the Zurich University of Applied Sciences (ZHAW), as well as head of the Information Engineering group that is located at the Institute of Applied Information Technology. His main research interests are in the field of unstructured information, specifically information retrieval evaluation, cross-language information retrieval, and natural language processing. He was one of the original initiators of the CLEF campaigns, which are the largest European forum for benchmarking of systems from the area of information retrieval and related fields. Prior to joining ZHAW, he served as head of research and innovation at Eurospider Information Technology AG, Zurich, Switzerland, a vendor of information retrieval solutions, and has thus extensive experience in the transfer of state-of-the-art technology to the commercial marketplace. Prof. Dr. Thilo Stadelmann is a senior lecturer in computer science at ZHAW School of Engineering in Winterthur. His current research focuses on applications of machine learning, especially deep learning, to diverse kinds of data. He is head of the ZHAW Data Science Laboratory and member of the board of the Swiss Alliance for Data-Intensive Services. Before joining ZHAW, Thilo headed a team of software developers and data miners at TWT GmbH Science & Innovation, developing tailor-made data management applications for the German automotive industry. He has more than 10 years of experience as a professional software developer. Prof. Dr. Kurt Stockinger is a senior lecturer in computer science at ZHAW and Director of Studies in Data Science. His research focuses on data warehousing (DWH), business intelligence (BI) and Big Data. He is also on the Advisory Board of Callista Group AG. Before joining ZHAW, Kurt was a DWH and BI Architect at Credit Suisse, Zurich where he worked on designing and implementing algorithmsfor a terabyte-scale enterprise data warehouse, data security, and DWH/BI applications. Prior, Kurt worked for four years at Lawrence Berkeley National Laboratory performing research on multi-dimensional indexing and query methods for large-scale scientific data as well as high-performance visual analytics. From 2000 to 2003 Kurt was heading the Replica Optimization Team of the EU Data Grid Project at CERN. In 2001 Kurt was a visiting researcher at California Institute of Technology.

• Preface.- 1 Introduction.- 2 Data Science.- 3 Data Scientists.- 4 Data products.- 5 Legal Aspects of Applied Data Science.- 6 Risks and Side Effects of Data Science and Data Technology.- 7 Organization.- 8 What is Data Science?.- 9 On Developing Data Science.- 10 The ethics of Big Data applications in the consumer sector.- 11 Statistical Modelling.- 12 Beyond ImageNet - Deep Learning in Industrial Practice.- 13 THE BEAUTY OF SMALL DATA - AN INFORMATION RETRIEVAL PERSPECTIVE.- 14 Narrative Visualization of Open Data.- 15 Security of Data Science and Data Science for Security.- 16 Online Anomaly Detection over Big Data Streams.- 17 Unsupervised Learning and Simulation for Complexity Management in Business Operations.- 18 Data Warehousing and Exploratory Analysis for Market Monitoring.- 19 Mining Person-Centric Datasets for Insight, Prediction, and Public Health Planning.- 20 Economic Measures of Forecast Accuracy for Demand Planning - A Case-Based Discussion.- 21 Large-Scale Data-DrivenFinancial Risk Assessment.- 22 Governance and IT Architecture.- 23 Image Analysis at Scale for Finding the Links between Structure and Biology.- 24 Lessons Learned from Challenging Data Science Case Studies.