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A Comprehensive Review of Unstructured Data Management Approaches in Data Warehouse

机译:数据仓库中非结构化数据管理方法的全面回顾

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The amount of business data is large & keeps on evolving leading to heterogeneous information base. The challenge is to access, analyze & integrate various data sources for making intelligent decisions. Business data can be structured or unstructured. Structured data attains the row-column format easily while unstructured data (USD) is the one that poses problem in such kind of tabular storage. Owing to the fact that USD is more than three times of structured data, and that it is more resourceful business wise and helps in charting out strategies and making decisions, it becomes important to devise methods for handling USD in data warehouse. Since the importance of USD has been realized, various authors have discussed different ways to manage it and extract useful information from it. In this paper, we have first comprehensively reviewed & surveyed the representative research works of various authors that have demonstrated how unstructured data can be handled in the warehouse. Finally, we have manifested & sorted them on various parameters & provided the same in tabular form.
机译:业务数据量很大,并且不断发展,导致异构信息库。挑战在于访问,分析和集成各种数据源以做出明智的决策。业务数据可以是结构化的,也可以是非结构化的。结构化数据很容易达到行-列格式,而非结构化数据(USD)是在这种表格存储中带来问题的一种。由于USD是结构化数据的三倍以上,并且它是更明智的业务策略,并且有助于制定策略和制定决策,因此设计用于在数据仓库中处理USD的方法变得很重要。由于人们意识到美元的重要性,因此许多作者讨论了不同的管理方式和从中提取有用信息的方法。在本文中,我们首先对各个作者的代表性研究工作进行了全面的回顾和调查,这些研究表明了如何在仓库中处理非结构化数据。最后,我们在各种参数上对它们进行了显示和排序,并以表格形式提供了相同的内容。

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