Data Modeling and Data Analytics: A Survey from a Big Data Perspective
Data Modeling and Data Analytics: A Survey from a Big Data Perspective
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DOI：
10.4236/jsea.2015.812058
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发表时间：
2015-12
期刊：
影响因子：
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通讯作者：
André Ribeiro;Afonso Silva;A. Silva
中科院分区：
文献类型：
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作者：
André Ribeiro;Afonso Silva;A. Silva
最近几年，我们见证了数据量和可用性的巨大增长。这一事实主要源于大量来源（如计算机、移动设备、传感器或社交网络）的出现，这些来源不断产生结构化、半结构化或非结构化数据。数据库管理系统和数据仓库不再是用于存储和分析数据集的唯一技术，这是因为当今数据的数量和复杂结构降低了它们的性能和可扩展性。大数据是最近的挑战之一，因为它在数据存储、处理和可视化方面提出了新的要求。尽管如此，正确地分析大数据可以构成巨大的优势，因为它允许发现数据集中的模式和相关性。用户可以使用这些处理过的信息来获得更深入的见解并获得业务优势。因此，数据建模和数据分析的发展方式使我们能够在不影响性能和可用性的情况下处理大量数据，而不是通过“放松”通常的ACID属性。本文对这一主题的现状进行了广泛的讨论，特别关注数据建模和数据分析，描述和澄清了三种主要方法在这些方面的主要区别，即：操作数据库、决策支持数据库和大数据技术。
These last years we have been witnessing a tremendous growth in the volume and availability of data. This fact results primarily from the emergence of a multitude of sources (e.g. computers, mobile devices, sensors or social networks) that are continuously producing either structured, semi-structured or unstructured data. Database Management Systems and Data Warehouses are no longer the only technologies used to store and analyze datasets, namely due to the volume and complex structure of nowadays data that degrade their performance and scalability. Big Data is one of the recent challenges, since it implies new requirements in terms of data storage, processing and visualization. Despite that, analyzing properly Big Data can constitute great advantages because it allows discovering patterns and correlations in datasets. Users can use this processed information to gain deeper insights and to get business advantages. Thus, data modeling and data analytics are evolved in a way that we are able to process huge amounts of data without compromising performance and availability, but instead by “relaxing” the usual ACID properties. This paper provides a broad view and discussion of the current state of this subject with a particular focus on data modeling and data analytics, describing and clarifying the main differences between the three main approaches in what concerns these aspects, namely: operational databases, decision support databases and Big Data technologies.