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Improving the User Experience through Practical Data Analytics is your must-have resource for making UX design decisions based on data, rather than hunches. Authors Fritz and Berger help the UX professional recognize and understand the enormous potential of the ever-increasing user data that is often accumulated as a by-product of routine UX tasks, such as conducting usability tests, launching surveys, or reviewing clickstream information. Then, step-by-step, they explain how to utilize both descriptive and predictive statistical techniques to gain meaningful insight with that data. You'll be

Computer games -- Development. --- Data mining. --- Web sites -- Design -- Management. --- Web sites -- Design -- Planning. --- Engineering & Applied Sciences --- Computer Science --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching

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Big Data in medical science - what exactly is that? What are the potentials for healthcare management? Where is Big Data at the moment? Which risk factors need to be kept in mind? What is hype and what is real potential? This book provides an impression of the new possibilities of networked data analysis and "Big Data" - for and within medical science and healthcare management. Big Data is about the collection, storage, search, distribution, statistical analysis and visualization of large amounts of data. This is especially relevant in healthcare management, as the amount of digital information is growing exponentially. An amount of data corresponding to 12 million novels emerges during the time of a single hospital stay. These are dimensions that cannot be dealt with without IT technologies. What can we do with the data that are available today? What will be possible in the next few years? Do we want everything that is possible? Who protects the data from wrong usage? More importantly, who protects the data from NOT being used? Big Data is the "resource of the 21st century" and might change the world of medical science more than we understand, realize and want at the moment. The core competence of Big Data will be the complete and correct collection, evaluation and interpretation of data. This also makes it possible to estimate the frame conditions and possibilities of the automation of daily (medical) routine. Can Big Data in medical science help to better understand fundamental problems of health and illness, and draw consequences accordingly? Big Data also means the overcoming of sector borders in healthcare management. The specialty of Big Data analysis will be the new quality of the outcomes of the combination of data that were not related before. That is why the editor of the book gives a voice to 30 experts, working in a variety of fields, such as in hospitals, in health insurance or as medical practitioners. The authors show potentials, risks, concrete practical examples, future scenarios, and come up with possible answers for the field of information technology and data privacy.

Medicine --- Data mining. --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Health Workforce --- Research. --- Big Data. --- data protection. --- healthcare management.

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Information visualization --- Data mining --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Data visualization --- Visualization of information --- Information science --- Visual analytics --- Computer programs. --- SAP Lumira.

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Today, the generation and use of huge volumes of data are redefining our “intelligence” capacity and our social and economic landscapes, spurring new industries, processes and products, and creating significant competitive advantages. In this sense, data-driven innovation (DDI) has become a key pillar of 21st-century growth, with the potential to significantly enhance productivity, resource efficiency, economic competitiveness, and social well-being. Greater access to and use of data create a wide array of impacts and policy challenges, ranging from privacy and consumer protection to open access issues and measurement concerns, across public and private health, legal and science domains. This report aims to improve the evidence base on the role of DDI for promoting growth and well-being, and provide policy guidance on how to maximise the benefits of DDI and mitigate the associated economic and societal risks.

Science and Technology --- Big data --- Data mining --- Technological innovations --- Information technology --- Economic aspects. --- Social aspects. --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Data sets, Large --- Large data sets --- Data sets

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econometric methodology --- finance applications --- asset pricing --- financial predictablility --- economics --- data science --- Finance --- Data mining --- Machine learning --- Data mining. --- Data processing --- Data processing. --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Learning, Machine --- Artificial intelligence --- Machine theory --- Funding --- Funds --- Economics --- Currency question --- Machine learning. --- Financial Management & Planning