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Data mining is an area of research where appropriate methodological research and technical means are experienced to produce useful knowledge from different types of data. Data mining techniques use a broad family of computationally intensive methods that include decision trees, neural networks, rule induction, machine learning and graphic visualization. This book discusses the principles, applications and emerging challenges of data mining.

Data mining. --- 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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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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In 2011, the World Bank Group commenced a multiyear program designed to support countries in systematically examining and strengthening the performance of their education system. Part of the World Bank's new Education Section Strategy, this evidence-based initiative, called SABER (Systems Approach for Better Education Results), is building a toolkit of diagnostics for examining education system and their component policy domains against global standards and best practices of countries around the world. The objectives of this report are to examine the system according to key policy areas, identify successes and challenges in the system, and provide recommendations to support the advancement of EMIS in Solomon Islands. Recommendations and activities aim to improve overall EMIS functionality in a sustainable and effective manner to ensure better access and use of information for decision making, planning, and student learning. This profile summarizes key points are as follows: Institutionalization of EMIS as the core management information system of the government will require strong policies and a dedicated EMIS budget. The policy should include clearly outlined mandatory practices to be adopted by various education stakeholders at each level of the education system. Efforts should be made to improve the local capacity of EMIS staff by investing in their professional development activities. EAs should be involved in the process of data collection, processing, and dissemination. The type of data collected and indicators produced by EMIS must be reviewed and further developed to include student level data. Integration of other education databases into EMIS will result in more effective utilization of education data for decision making. EMIS needs to be supported by regular internal and external audits to improve the accuracy of data collected and utilized indecision making. The quality of feedback reports sent to schools should be enriched with more relevant micro level information on school performance. Clearly articulated data utilization and dissemination strategies need to be developed, including processes to ensure the timely production of an annual statistics handbook, as well as additional utilization and dissemination opportunities such as pamphlets and web-based portals.

Access to Education --- Business --- Confidentiality --- Data analysis --- Databases --- Education --- Education For All --- Electricity --- Hardware --- Human Resources --- Ict Policy and Strategies --- Information and Communication Technologies --- Knowledge for Development --- Legal Framework --- Newsletters --- Privacy --- Project Management --- Protocols --- Schools --- Software --- Teachers