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Advances and Research Directions in Data-Warehousing Technology

机译:数据仓库技术的进展与研究方向

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摘要

Information is one of the most valuable assets of an organisation and when used properly can assist in intelligent decision making that can significantly improve the functioning of an organisation. Data Warehousing is a recent technology that allows information to be easily and efficiently accessed for decision-making activities by collecting data from many operational, legacy and possibly heterogeneous data sources. On-Line Analytical Processing (OLAP) tools are well-suited for complex data analysis, such as multi-dimensional data analysis, and to assist in decision support activities while data mining tools take the process one step further and actively search the data for patterns and hidden knowledge in the data held in the warehouse. Many organisations are building, or are planning to develop, a data warehouse for their operational and decision support needs. In this paper, we present an overview of data warehousing, multi-dimensional databases, OLAP and data mining technology and discuss the directions of current research in the area. We also discuss recent developments in data warehouse modelling, view selection and maintenance, indexing schemes, parallel query processing and data mining issues. A number of technical issues for exploratory research are presented and possible solutions are also discussed.
机译:信息是组织最有价值的资产之一,如果使用得当,可以帮助做出明智的决策,从而可以显着改善组织的功能。数据仓库是一种最新的技术,通过从许多可操作的,遗留的和可能是异构的数据源中收集数据,可以轻松有效地访问信息以进行决策活动。在线分析处理(OLAP)工具非常适合复杂数据分析(例如多维数据分析),并有助于决策支持活动,而数据挖掘工具则使过程更进一步并积极地在数据中搜索模式和隐藏在仓库中的数据中的知识。许多组织正在建立或计划开发满足其运营和决策支持需求的数据仓库。在本文中,我们概述了数据仓库,多维数据库,OLAP和数据挖掘技术,并讨论了该领域当前的研究方向。我们还将讨论数据仓库建模,视图选择和维护,索引方案,并行查询处理和数据挖掘问题的最新发展。提出了许多用于探索性研究的技术问题,并讨论了可能的解决方案。

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