TY - GEN
T1 - The formal model for multiversion data warehouse evolution
AU - Solodovnikova, Darja
PY - 2009
Y1 - 2009
N2 - Schemata of data warehouses often need to be adapted because of evolving business requirements or changes in data sources. To accumulate the history of schemata and data, it is possible to maintain multiple versions of data warehouse schemata. We propose the formal model to store the data about data warehouse logical and physical schemata and their versions. For each modification of a data warehouse schema, we outline the changes that need to be made to the formal model. We present the data warehouse framework that is able to track evolution process and adapt data warehouse schemata and data extraction, transformation and loading (ETL) processes.
AB - Schemata of data warehouses often need to be adapted because of evolving business requirements or changes in data sources. To accumulate the history of schemata and data, it is possible to maintain multiple versions of data warehouse schemata. We propose the formal model to store the data about data warehouse logical and physical schemata and their versions. For each modification of a data warehouse schema, we outline the changes that need to be made to the formal model. We present the data warehouse framework that is able to track evolution process and adapt data warehouse schemata and data extraction, transformation and loading (ETL) processes.
KW - Data warehouse evolution
KW - Formal model
KW - Schema versioning
UR - https://www.scopus.com/pages/publications/72749119729
U2 - 10.3233/978-1-58603-939-4-91
DO - 10.3233/978-1-58603-939-4-91
M3 - Conference paper
AN - SCOPUS:72749119729
SN - 9781586039394
T3 - Frontiers in Artificial Intelligence and Applications
SP - 91
EP - 102
BT - Databases and Information Systems V
PB - IOS Press
ER -