Data Warehousing in an Industrial Software Development Environment

Data quality is one of the bases for effective data mining. Flexible, consistent and extensible data storage is one of the requirements for effective data analysis. For more than 15 years, researchers in the database and decision making world have been studying the construction of data repositories...

Full description

Saved in:
Bibliographic Details
Main Authors: Colaco Junior, Methanias, Mendonca, Manoel, Rodrigues, Francisco
Format: Conference Proceeding
Language:English
Subjects:
Data mining
History
Maintenance engineering
Measurement
Mining Software Repositories
Software
Software Data Warehouse
Software engineering
Software Engineering Intelligence
Warehousing
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by
cites
container_end_page 135
container_issue
container_start_page 131
container_title
container_volume
creator Colaco Junior, Methanias
Mendonca, Manoel
Rodrigues, Francisco
description Data quality is one of the bases for effective data mining. Flexible, consistent and extensible data storage is one of the requirements for effective data analysis. For more than 15 years, researchers in the database and decision making world have been studying the construction of data repositories for data analysis. Named data warehouses, these repositories are historical databases, which are separated both logically and physically from the organization production environment and designed to store data gathered from this environment. Data warehousing also includes data selection, integration and organization approaches to make data easily accessible to the decision making process. Based on our previous experience with data warehousing for mining software repositories, this paper presents a Data Warehousing Approach for software development data analysis.
doi_str_mv 10.1109/SEW.2009.7
format conference_proceeding
fullrecord <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_5621799</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>5621799</ieee_id><sourcerecordid>5621799</sourcerecordid><originalsourceid>FETCH-LOGICAL-i90t-a60a9dbdbb6bf1e8c880bf7615e5637f197c41bc38d98a9b7b88fb39f4e2d1643</originalsourceid><addsrcrecordid>eNo1j01Lw0AYhFdUsNZcvHrZP5C6m_18j9pGLRQ8tNBj2U3e1ZV0U5K04r83os5l5oFhYAi55WzGOYP7dbmdFYzBzJyRDIzlspBSWy3VObn-BwEXZMKVYrkuuLoiWd9_sFFSFaBgQh4XbnB06zp8b499TG80JuoSXab62A9ddA1dt2H4HAt0gSds2sMe00DLdIpdm37yDbkMrukx-_Mp2TyVm_lLvnp9Xs4fVnkENuROMwe1r73XPnC0lbXMB6O5QqWFCRxMJbmvhK3BOvDGWxu8gCCxqLmWYkrufmcjIu4OXdy77munxlsGQHwDBoBMSA</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Data Warehousing in an Industrial Software Development Environment</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Colaco Junior, Methanias ; Mendonca, Manoel ; Rodrigues, Francisco</creator><creatorcontrib>Colaco Junior, Methanias ; Mendonca, Manoel ; Rodrigues, Francisco</creatorcontrib><description>Data quality is one of the bases for effective data mining. Flexible, consistent and extensible data storage is one of the requirements for effective data analysis. For more than 15 years, researchers in the database and decision making world have been studying the construction of data repositories for data analysis. Named data warehouses, these repositories are historical databases, which are separated both logically and physically from the organization production environment and designed to store data gathered from this environment. Data warehousing also includes data selection, integration and organization approaches to make data easily accessible to the decision making process. Based on our previous experience with data warehousing for mining software repositories, this paper presents a Data Warehousing Approach for software development data analysis.</description><identifier>ISSN: 1550-6215</identifier><identifier>ISBN: 1424468639</identifier><identifier>ISBN: 9781424468638</identifier><identifier>EISBN: 9781424468645</identifier><identifier>EISBN: 1424468647</identifier><identifier>DOI: 10.1109/SEW.2009.7</identifier><language>eng</language><publisher>IEEE</publisher><subject>Data mining ; History ; Maintenance engineering ; Measurement ; Mining Software Repositories ; Software ; Software Data Warehouse ; Software engineering ; Software Engineering Intelligence ; Warehousing</subject><ispartof>2009 33rd Annual IEEE Software Engineering Workshop, 2009, p.131-135</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/5621799$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,27925,54555,54920,54932</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5621799$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Colaco Junior, Methanias</creatorcontrib><creatorcontrib>Mendonca, Manoel</creatorcontrib><creatorcontrib>Rodrigues, Francisco</creatorcontrib><title>Data Warehousing in an Industrial Software Development Environment</title><title>2009 33rd Annual IEEE Software Engineering Workshop</title><addtitle>SEW</addtitle><description>Data quality is one of the bases for effective data mining. Flexible, consistent and extensible data storage is one of the requirements for effective data analysis. For more than 15 years, researchers in the database and decision making world have been studying the construction of data repositories for data analysis. Named data warehouses, these repositories are historical databases, which are separated both logically and physically from the organization production environment and designed to store data gathered from this environment. Data warehousing also includes data selection, integration and organization approaches to make data easily accessible to the decision making process. Based on our previous experience with data warehousing for mining software repositories, this paper presents a Data Warehousing Approach for software development data analysis.</description><subject>Data mining</subject><subject>History</subject><subject>Maintenance engineering</subject><subject>Measurement</subject><subject>Mining Software Repositories</subject><subject>Software</subject><subject>Software Data Warehouse</subject><subject>Software engineering</subject><subject>Software Engineering Intelligence</subject><subject>Warehousing</subject><issn>1550-6215</issn><isbn>1424468639</isbn><isbn>9781424468638</isbn><isbn>9781424468645</isbn><isbn>1424468647</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2009</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNo1j01Lw0AYhFdUsNZcvHrZP5C6m_18j9pGLRQ8tNBj2U3e1ZV0U5K04r83os5l5oFhYAi55WzGOYP7dbmdFYzBzJyRDIzlspBSWy3VObn-BwEXZMKVYrkuuLoiWd9_sFFSFaBgQh4XbnB06zp8b499TG80JuoSXab62A9ddA1dt2H4HAt0gSds2sMe00DLdIpdm37yDbkMrukx-_Mp2TyVm_lLvnp9Xs4fVnkENuROMwe1r73XPnC0lbXMB6O5QqWFCRxMJbmvhK3BOvDGWxu8gCCxqLmWYkrufmcjIu4OXdy77munxlsGQHwDBoBMSA</recordid><startdate>200910</startdate><enddate>200910</enddate><creator>Colaco Junior, Methanias</creator><creator>Mendonca, Manoel</creator><creator>Rodrigues, Francisco</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>200910</creationdate><title>Data Warehousing in an Industrial Software Development Environment</title><author>Colaco Junior, Methanias ; Mendonca, Manoel ; Rodrigues, Francisco</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-a60a9dbdbb6bf1e8c880bf7615e5637f197c41bc38d98a9b7b88fb39f4e2d1643</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Data mining</topic><topic>History</topic><topic>Maintenance engineering</topic><topic>Measurement</topic><topic>Mining Software Repositories</topic><topic>Software</topic><topic>Software Data Warehouse</topic><topic>Software engineering</topic><topic>Software Engineering Intelligence</topic><topic>Warehousing</topic><toplevel>online_resources</toplevel><creatorcontrib>Colaco Junior, Methanias</creatorcontrib><creatorcontrib>Mendonca, Manoel</creatorcontrib><creatorcontrib>Rodrigues, Francisco</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Colaco Junior, Methanias</au><au>Mendonca, Manoel</au><au>Rodrigues, Francisco</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Data Warehousing in an Industrial Software Development Environment</atitle><btitle>2009 33rd Annual IEEE Software Engineering Workshop</btitle><stitle>SEW</stitle><date>2009-10</date><risdate>2009</risdate><spage>131</spage><epage>135</epage><pages>131-135</pages><issn>1550-6215</issn><isbn>1424468639</isbn><isbn>9781424468638</isbn><eisbn>9781424468645</eisbn><eisbn>1424468647</eisbn><abstract>Data quality is one of the bases for effective data mining. Flexible, consistent and extensible data storage is one of the requirements for effective data analysis. For more than 15 years, researchers in the database and decision making world have been studying the construction of data repositories for data analysis. Named data warehouses, these repositories are historical databases, which are separated both logically and physically from the organization production environment and designed to store data gathered from this environment. Data warehousing also includes data selection, integration and organization approaches to make data easily accessible to the decision making process. Based on our previous experience with data warehousing for mining software repositories, this paper presents a Data Warehousing Approach for software development data analysis.</abstract><pub>IEEE</pub><doi>10.1109/SEW.2009.7</doi><tpages>5</tpages></addata></record>
fulltext fulltext_linktorsrc
identifier ISSN: 1550-6215
ispartof 2009 33rd Annual IEEE Software Engineering Workshop, 2009, p.131-135
issn 1550-6215
language eng
recordid cdi_ieee_primary_5621799
source IEEE Electronic Library (IEL) Conference Proceedings
subjects Data mining
History
Maintenance engineering
Measurement
Mining Software Repositories
Software
Software Data Warehouse
Software engineering
Software Engineering Intelligence
Warehousing
title Data Warehousing in an Industrial Software Development Environment
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-06T18%3A02%3A59IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Data%20Warehousing%20in%20an%20Industrial%20Software%20Development%20Environment&rft.btitle=2009%2033rd%20Annual%20IEEE%20Software%20Engineering%20Workshop&rft.au=Colaco%20Junior,%20Methanias&rft.date=2009-10&rft.spage=131&rft.epage=135&rft.pages=131-135&rft.issn=1550-6215&rft.isbn=1424468639&rft.isbn_list=9781424468638&rft_id=info:doi/10.1109/SEW.2009.7&rft.eisbn=9781424468645&rft.eisbn_list=1424468647&rft_dat=%3Cieee_6IE%3E5621799%3C/ieee_6IE%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-i90t-a60a9dbdbb6bf1e8c880bf7615e5637f197c41bc38d98a9b7b88fb39f4e2d1643%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=5621799&rfr_iscdi=true