Research Article

Schema Evolution for Data Warehouse: A Survey

by  Meenakshi Arora, Anjana Gosain
journal cover
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 22 - Issue 6
Published: May 2011
Authors: Meenakshi Arora, Anjana Gosain
10.5120/2590-3588
PDF

Meenakshi Arora, Anjana Gosain . Schema Evolution for Data Warehouse: A Survey. International Journal of Computer Applications. 22, 6 (May 2011), 6-14. DOI=10.5120/2590-3588

                        @article{ 10.5120/2590-3588,
                        author  = { Meenakshi Arora,Anjana Gosain },
                        title   = { Schema Evolution for Data Warehouse: A Survey },
                        journal = { International Journal of Computer Applications },
                        year    = { 2011 },
                        volume  = { 22 },
                        number  = { 6 },
                        pages   = { 6-14 },
                        doi     = { 10.5120/2590-3588 },
                        publisher = { Foundation of Computer Science (FCS), NY, USA }
                        }
                        %0 Journal Article
                        %D 2011
                        %A Meenakshi Arora
                        %A Anjana Gosain
                        %T Schema Evolution for Data Warehouse: A Survey%T 
                        %J International Journal of Computer Applications
                        %V 22
                        %N 6
                        %P 6-14
                        %R 10.5120/2590-3588
                        %I Foundation of Computer Science (FCS), NY, USA
Abstract

Data warehouse is considered as the core component of the modern decision support systems. Due to the major support of data warehouse in the daily transaction of an enterprise, the requirements for the design and the implementation of DW are dynamic and subjective. This dynamic nature of the data warehouse may reflect the evolution in the data warehouse. Data warehouse evolution may be focused on three approaches namely schema evolution, schema versioning and view maintenance. Evolution of the data warehouse may often change their data and structure (schema changes). These schema changes may be consider according to the change in structure, software and users’ requirement. Schema evolution in data warehouse consists of various level namely structural level, conceptual level and behavioural level. This paper mainly focuses on schema evolution and proposes the operators to handle the creation and evolution of aggregated fact table. Our work is to do comparative study for various approaches of schema evolution.

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

Data Warehouse Evolution Schema Evolution Schema Operators Aggregate operator

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