Australasian Journal of Information Systems | |
Advances and Research Directions in Data-Warehousing Technology | |
John Roddick1  Mukesh Mohania1  Sunil Samtani1  Yahiko Kambayashi1  | |
[1] Mukesh Mohania | |
关键词: object orientation; inheritance; redundancy; CASE; quality; | |
DOI : 10.3127/ajis.v7i1.287 | |
学科分类:计算机科学(综合) | |
来源: University of Canberra * Faculty of Information Sciences and Engineering | |
【 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.
【 授权许可】
Unknown
【 预 览 】
Files | Size | Format | View |
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RO201912020430734ZK.pdf | 1711KB | download |