Dynamic Multidimensional Data Cubes for Interactive Analysis of Massive Datasets

Dynamic Multidimensional Data Cubes for Interactive Analysis of Massive Datasets

Mirek Riedewald (Cornell University, USA) and Divyakant Agrawal (University of California, Santa Barbara, USA)
DOI: 10.4018/978-1-59140-553-5.ch162
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Abstract

Rapidly improving computing and networking technology enables enterprises to collect data from virtually all its business units. The main challenge today is to extract useful information from an overwhelmingly large amount of raw data. To support complex analysis queries, data warehouses were introduced. They manage data, which is extracted from the different operational databases and from external data sources, and they are optimized for fast query processing. For modern data warehouses, it is common to manage Terabytes of data. According to a recent survey by the Winter CorporationĀ (2003), for instance, the decision support database of SBC reached a size of almost 25 Terabytes, up from 10.5 Terabytes in 2001 (Winter Corporation, 2001).

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