{"title":"半实时数据仓库的数据负载分配","authors":"M. Javed, A. Nawaz","doi":"10.1109/ICCNT.2010.104","DOIUrl":null,"url":null,"abstract":"Today many organizations used data warehouse for strategic decision making. Today's real-time business stresses the potential to process increasingly volumes of data at very high speed in order to stay competitive in market. Data Warehouse is populated by data extraction, transformation and loading from different data sources by software utilities called ETL (Extraction, transformation & loading). ETL process is a time consuming process as it has to process large volume of data. ETL processes must have certain completion time window and ETL process must have to finish within this time window. In this paper we discusses a technique to distribute the volume of data to be extracted, transformed and loaded into data warehouse by merging both conventional and real-time techniques, so ETL process finishes its job within its time window by utilizing ETL idle time.","PeriodicalId":135847,"journal":{"name":"2010 Second International Conference on Computer and Network Technology","volume":"59 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Data Load Distribution by Semi Real Time Data Warehouse\",\"authors\":\"M. Javed, A. Nawaz\",\"doi\":\"10.1109/ICCNT.2010.104\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Today many organizations used data warehouse for strategic decision making. Today's real-time business stresses the potential to process increasingly volumes of data at very high speed in order to stay competitive in market. Data Warehouse is populated by data extraction, transformation and loading from different data sources by software utilities called ETL (Extraction, transformation & loading). ETL process is a time consuming process as it has to process large volume of data. ETL processes must have certain completion time window and ETL process must have to finish within this time window. In this paper we discusses a technique to distribute the volume of data to be extracted, transformed and loaded into data warehouse by merging both conventional and real-time techniques, so ETL process finishes its job within its time window by utilizing ETL idle time.\",\"PeriodicalId\":135847,\"journal\":{\"name\":\"2010 Second International Conference on Computer and Network Technology\",\"volume\":\"59 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-04-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 Second International Conference on Computer and Network Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCNT.2010.104\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Second International Conference on Computer and Network Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCNT.2010.104","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Data Load Distribution by Semi Real Time Data Warehouse
Today many organizations used data warehouse for strategic decision making. Today's real-time business stresses the potential to process increasingly volumes of data at very high speed in order to stay competitive in market. Data Warehouse is populated by data extraction, transformation and loading from different data sources by software utilities called ETL (Extraction, transformation & loading). ETL process is a time consuming process as it has to process large volume of data. ETL processes must have certain completion time window and ETL process must have to finish within this time window. In this paper we discusses a technique to distribute the volume of data to be extracted, transformed and loaded into data warehouse by merging both conventional and real-time techniques, so ETL process finishes its job within its time window by utilizing ETL idle time.
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