TATS: An efficient technique for computing temporal aggregates for data warehousing

Young O. Shin, Sung Kong Park, Doo Kwon Baik, Keun H. Ryu

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

An important use of data warehousing is to provide temporal views over the history of source data. It is significant that nearly all data warehouses are dependent on relational database technology, yet relational databases provide little or no real support for temporal data. Therefore, it is difficult to obtain accurate information for time-varying data. In this paper, we are going to design a temporal data warehouse to support time-varying data efficiently. For this purpose, we present a method to support temporal query by combining a temporal query process layer with the relational database which is used as a source database in an existing data warehouse. We introduce the Temporal Aggregate Tree Strategy (TATS), and suggest its algorithm for the way to aggregate the time-varying data that is changed by the time when the temporal view is created. In addition, The TATS and the materialized view creation method of the existing data warehouse have been evaluated. As a result, the TATS reduces the size of the fact table and it shows a good performance for the comparison factor in case of processing the query for time-varying data.

Original languageEnglish
Pages (from-to)41-50
Number of pages10
JournalETRI Journal
Volume22
Issue number3
Publication statusPublished - 2000 Sep 1

Fingerprint

Data warehouses
Processing

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering

Cite this

TATS : An efficient technique for computing temporal aggregates for data warehousing. / Shin, Young O.; Park, Sung Kong; Baik, Doo Kwon; Ryu, Keun H.

In: ETRI Journal, Vol. 22, No. 3, 01.09.2000, p. 41-50.

Research output: Contribution to journalArticle

Shin, Young O. ; Park, Sung Kong ; Baik, Doo Kwon ; Ryu, Keun H. / TATS : An efficient technique for computing temporal aggregates for data warehousing. In: ETRI Journal. 2000 ; Vol. 22, No. 3. pp. 41-50.
@article{1e3167536b6f4f8f897e70486a341f9c,
title = "TATS: An efficient technique for computing temporal aggregates for data warehousing",
abstract = "An important use of data warehousing is to provide temporal views over the history of source data. It is significant that nearly all data warehouses are dependent on relational database technology, yet relational databases provide little or no real support for temporal data. Therefore, it is difficult to obtain accurate information for time-varying data. In this paper, we are going to design a temporal data warehouse to support time-varying data efficiently. For this purpose, we present a method to support temporal query by combining a temporal query process layer with the relational database which is used as a source database in an existing data warehouse. We introduce the Temporal Aggregate Tree Strategy (TATS), and suggest its algorithm for the way to aggregate the time-varying data that is changed by the time when the temporal view is created. In addition, The TATS and the materialized view creation method of the existing data warehouse have been evaluated. As a result, the TATS reduces the size of the fact table and it shows a good performance for the comparison factor in case of processing the query for time-varying data.",
author = "Shin, {Young O.} and Park, {Sung Kong} and Baik, {Doo Kwon} and Ryu, {Keun H.}",
year = "2000",
month = "9",
day = "1",
language = "English",
volume = "22",
pages = "41--50",
journal = "ETRI Journal",
issn = "1225-6463",
publisher = "ETRI",
number = "3",

}

TY - JOUR

T1 - TATS

T2 - An efficient technique for computing temporal aggregates for data warehousing

AU - Shin, Young O.

AU - Park, Sung Kong

AU - Baik, Doo Kwon

AU - Ryu, Keun H.

PY - 2000/9/1

Y1 - 2000/9/1

N2 - An important use of data warehousing is to provide temporal views over the history of source data. It is significant that nearly all data warehouses are dependent on relational database technology, yet relational databases provide little or no real support for temporal data. Therefore, it is difficult to obtain accurate information for time-varying data. In this paper, we are going to design a temporal data warehouse to support time-varying data efficiently. For this purpose, we present a method to support temporal query by combining a temporal query process layer with the relational database which is used as a source database in an existing data warehouse. We introduce the Temporal Aggregate Tree Strategy (TATS), and suggest its algorithm for the way to aggregate the time-varying data that is changed by the time when the temporal view is created. In addition, The TATS and the materialized view creation method of the existing data warehouse have been evaluated. As a result, the TATS reduces the size of the fact table and it shows a good performance for the comparison factor in case of processing the query for time-varying data.

AB - An important use of data warehousing is to provide temporal views over the history of source data. It is significant that nearly all data warehouses are dependent on relational database technology, yet relational databases provide little or no real support for temporal data. Therefore, it is difficult to obtain accurate information for time-varying data. In this paper, we are going to design a temporal data warehouse to support time-varying data efficiently. For this purpose, we present a method to support temporal query by combining a temporal query process layer with the relational database which is used as a source database in an existing data warehouse. We introduce the Temporal Aggregate Tree Strategy (TATS), and suggest its algorithm for the way to aggregate the time-varying data that is changed by the time when the temporal view is created. In addition, The TATS and the materialized view creation method of the existing data warehouse have been evaluated. As a result, the TATS reduces the size of the fact table and it shows a good performance for the comparison factor in case of processing the query for time-varying data.

UR - http://www.scopus.com/inward/record.url?scp=0034275335&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0034275335&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:0034275335

VL - 22

SP - 41

EP - 50

JO - ETRI Journal

JF - ETRI Journal

SN - 1225-6463

IS - 3

ER -