Data Science in Perspective

Rogerio Rossi
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Abstract

Data and Science has stood out in the generation of results, whether in the projects of the scientific domain or business domain. CERN Project, Scientific Institutes, companies like Walmart, Google, Apple, among others, need data to present their results and make predictions in the competitive data world. Data and Science are words that together culminated in a globally recognized term called Data Science. Data Science is in its initial phase, possibly being part of formal sciences and also being presented as part of applied sciences, capable of generating value and supporting decision making. Data Science considers science and, consequently, the scientific method to promote decision making through data intelligence. In many cases, the application of the method (or part of it) is considered in Data Science projects in scientific domain (social sciences, bioinformatics, geospatial projects) or business domain (finance, logistic, retail), among others. In this sense, this article addresses the perspectives of Data Science as a multidisciplinary area, considering science and the scientific method, and its formal structure which integrate Statistics, Computer Science, and Business Science, also taking into account Artificial Intelligence, emphasizing Machine Learning, among others. The article also deals with the perspective of applied Data Science, since Data Science is used for generating value through scientific and business projects. Data Science persona is also discussed in the article, concerning the education of Data Science professionals and its corresponding profiles, since its projection changes the field of data in the world.
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透视数据科学
无论是在科学领域还是在商业领域的项目中,Data and Science都在成果的产生中脱颖而出。欧洲核子研究中心项目、科学研究所、沃尔玛、谷歌、苹果等公司都需要数据来展示他们的结果,并在竞争激烈的数据世界中做出预测。“数据”和“科学”这两个词结合在一起,形成了一个全球公认的术语——“数据科学”。数据科学正处于初始阶段,可能是正式科学的一部分,也可能是应用科学的一部分,能够产生价值并支持决策。数据科学考虑科学,因此,通过数据智能促进决策的科学方法。在许多情况下,在科学领域(社会科学,生物信息学,地理空间项目)或商业领域(金融,物流,零售)等数据科学项目中考虑该方法(或其部分)的应用。从这个意义上说,本文将数据科学的观点视为一个多学科领域,考虑到科学和科学方法,以及整合统计学,计算机科学和商业科学的正式结构,也考虑到人工智能,强调机器学习等。本文还讨论了应用数据科学的观点,因为数据科学用于通过科学和商业项目创造价值。本文还讨论了数据科学角色,涉及数据科学专业人员的教育及其相应的概况,因为它的投影改变了世界上的数据领域。
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