Research Article

Refreshing Datawarehouse in Near Real-Time

by  Tanvi Jain, Rajasree S, Shivani Saluja
journal cover
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 46 - Issue 18
Published: May 2012
Authors: Tanvi Jain, Rajasree S, Shivani Saluja
10.5120/7042-9482
PDF

Tanvi Jain, Rajasree S, Shivani Saluja . Refreshing Datawarehouse in Near Real-Time. International Journal of Computer Applications. 46, 18 (May 2012), 24-29. DOI=10.5120/7042-9482

                        @article{ 10.5120/7042-9482,
                        author  = { Tanvi Jain,Rajasree S,Shivani Saluja },
                        title   = { Refreshing Datawarehouse in Near Real-Time },
                        journal = { International Journal of Computer Applications },
                        year    = { 2012 },
                        volume  = { 46 },
                        number  = { 18 },
                        pages   = { 24-29 },
                        doi     = { 10.5120/7042-9482 },
                        publisher = { Foundation of Computer Science (FCS), NY, USA }
                        }
                        %0 Journal Article
                        %D 2012
                        %A Tanvi Jain
                        %A Rajasree S
                        %A Shivani Saluja
                        %T Refreshing Datawarehouse in Near Real-Time%T 
                        %J International Journal of Computer Applications
                        %V 46
                        %N 18
                        %P 24-29
                        %R 10.5120/7042-9482
                        %I Foundation of Computer Science (FCS), NY, USA
Abstract

Data warehousing technology has made a huge impact in the world of business; it helps to turn data into information that helps analysts to make strategic decisions. Currently most data warehouse approaches employ static refresh mechanisms. But for various business requirements this is not an appropriate solution. Some critical data need to be refreshed in real time. We propose an approach to identify critical data by considering two factors, namely: a) impact from one update, b) number of records affected. The identified critical data will be stored in the temporary tables, these temporary tables will be refreshed in real time and remaining data will be refreshed in conventional way

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Index Terms
Computer Science
Information Sciences
No index terms available.
Keywords

Near Real-time Data Warehouse Change Data Capture (cdc) Extract Transform And Load (etl)

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