Managing and analyzing massive data sets with data cubes

  • Authors:

  • Mirek Riedewald;Divyakant Agrawal;Amr El Abbadi

  • Affiliations:

  • Computer Science Department, University of California, Santa Barbara CA;Computer Science Department, University of California, Santa Barbara CA;Computer Science Department, University of California, Santa Barbara CA

  • Venue:
  • Handbook of massive data sets
  • Year:
  • 2002

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Abstract

Data cubes combine an easy-to-understand conceptual model with an implementation that enables the fast summarization of large data sets. This makes them a powerful tool for supporting the interactive analysis of massive data collections like data warehouses and digital libraries. This article surveys some of the recent developments in data cube research. We mainly focus on techniques for fast aggregation in data warehousing environments. This includes work on group-by and range queries, approximate query responses, and compression. Since sparse high-dimensional data cubes are of increasing interest, issues related to them are explicitly discussed.