Curio: A Novel Solution for Efficient Storage and Indexing in Data Warehouses.
Anindya Datta, Krithi Ramamritham, Helen M. Thomas:
Curio: A Novel Solution for Efficient Storage and Indexing in Data Warehouses.
VLDB 1999: 730-733@inproceedings{DBLP:conf/vldb/DattaRT99,
author = {Anindya Datta and
Krithi Ramamritham and
Helen M. Thomas},
editor = {Malcolm P. Atkinson and
Maria E. Orlowska and
Patrick Valduriez and
Stanley B. Zdonik and
Michael L. Brodie},
title = {Curio: A Novel Solution for Efficient Storage and Indexing in
Data Warehouses},
booktitle = {VLDB'99, Proceedings of 25th International Conference on Very
Large Data Bases, September 7-10, 1999, Edinburgh, Scotland,
UK},
publisher = {Morgan Kaufmann},
year = {1999},
isbn = {1-55860-615-7},
pages = {730-733},
ee = {db/conf/vldb/DattaRT99.html},
crossref = {DBLP:conf/vldb/99},
bibsource = {DBLP, http://dblp.uni-trier.de}
}
BibTeX
Abstract
Data warehousing and On-Line Analytical Processing (OLAP)
are becoming critical components of decision support as
advances in technology are improving the ability to
manage and retrieve large volumes of data. Data warehousing
refers to ``a collection of decision support technologies
aimed at enabling the knowledge worker (executive, manager,
analyst) to make better and faster decisions'' [1].
OLAP refers to the technique of performing complex analysis
over the information stored in a data warehouse. It is often
used by management analysts and decision makers in a variety
of functional areas such as sales and marketing planning.
Typically, OLAP queries look for specific trends and anomalies
in the base information by aggregating, ranging, filtering and
grouping data in many different ways [8]. Efficient query
processing is a critical requirement for OLAP because the
underlying data warehouse is very large, queries are often
quite complex, and decision support applications typically
require interactive response times.
Copyright © 1999 by the VLDB Endowment.
Permission to copy without fee all or part of this material is granted provided that the copies are not made or
distributed for direct commercial advantage, the VLDB
copyright notice and the title of the publication and
its date appear, and notice is given that copying
is by the permission of the Very Large Data Base
Endowment. To copy otherwise, or to republish, requires
a fee and/or special permission from the Endowment.
Online Paper
DVD Version: Load ACM SIGMOD Anthology DVD 1" and ...
BibTeX
Printed Edition
Malcolm P. Atkinson, Maria E. Orlowska, Patrick Valduriez, Stanley B. Zdonik, Michael L. Brodie (Eds.):
VLDB'99, Proceedings of 25th International Conference on Very Large Data Bases, September 7-10, 1999, Edinburgh, Scotland, UK.
Morgan Kaufmann 1999, ISBN 1-55860-615-7
Contents BibTeX
References
- [1]
- Surajit Chaudhuri, Umeshwar Dayal:
An Overview of Data Warehousing and OLAP Technology.
SIGMOD Record 26(1): 65-74(1997) BibTeX
- [2]
- ...
- [3]
- Venky Harinarayan, Anand Rajaraman, Jeffrey D. Ullman:
Implementing Data Cubes Efficiently.
SIGMOD Conference 1996: 205-216 BibTeX
- [4]
- ...
- [5]
- Ralph Kimball:
The Data Warehouse Toolkit: Practical Techniques for Building Dimensional Data Warehouses.
John Wiley 1996, ISBN 0-471-15337-0
BibTeX
- [6]
- ...
- [7]
- Patrick E. O'Neil:
Model 204 Architecture and Performance.
HPTS 1987: 40-59 BibTeX
- [8]
- Patrick E. O'Neil, Dallan Quass:
Improved Query Performance with Variant Indexes.
SIGMOD Conference 1997: 38-49 BibTeX
- [9]
- ...
- [10]
- ...
- [11]
- ...
BibTeX
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