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Data Science is an interdisciplinary field about processes and systems to extract knowledge or insights from data in various forms, either structured or unstructured, which is a continuation of some of the data analysis fields such as statistics, data mining, and predictive analytics, similar to Knowledge Discovery in Databases (KDD). ==Overview== Data science employs techniques and theories drawn from many fields within the broad areas of mathematics, statistics, chemometrics, information science, and computer science, including signal processing, probability models, machine learning, statistical learning, data mining, database, data engineering, pattern recognition and learning, visualization, predictive analytics, uncertainty modeling, data warehousing, data compression, computer programming, artificial intelligence, and high performance computing. Methods that scale to Big Data are of particular interest in data science, although the discipline is not generally considered to be restricted to such big data, and big data solutions are often focused on organizing and preprocessing the data instead of analysis. The development of machine learning has enhanced the growth and importance of data science. Data science utilizes data preparation, statistics, predictive modeling and machine learning to investigate problems in various domains such as agriculture, marketing optimization, fraud detection, risk management, marketing analytics, public policy, etc. It emphasizes the use of general methods such as machine learning that apply without changes to multiple domains. This approach differs from traditional statistics with its emphasis on domain-specific knowledge and solutions. (The rationale is that developing tailored solutions does not scale.) Data scientists use their data and analytical ability to find and interpret rich data sources; manage large amounts of data despite hardware, software, and bandwidth constraints; merge data sources; ensure consistency of datasets; create visualizations to aid in understanding data; build mathematical models using the data; and present and communicate the data insights/findings. They are often expected to produce answers in days rather than months, work by exploratory analysis and rapid iteration, and to get/present results with dashboards (displays of current values) rather than papers/reports, as statisticians normally do. Data science affects academic and applied research in many domains, including machine translation, speech recognition, robotics, search engines, digital economy, but also the biological sciences, medical informatics, health care, social sciences and the humanities. It heavily influences economics, business and finance. From the business perspective, data science is an integral part of competitive intelligence, a newly emerging field that encompasses a number of activities, such as data mining and data analysis. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「data science」の詳細全文を読む スポンサード リンク
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