Authors : T.N. Manjunath and Ravindra S. Hegadi
Abstract: In current information trends, state of decision making is one of the important deeds for any organization or enterprise to identify them in the business market in this connection, the data which is present in data warehouse or decision databases should be very accurate and help them to give proper decisions. When the organizations or enterprises undergo a merger/takeover demands the data migration from legacy systems to modern systems/decision databases, i.e., target systems. If a target/decision databases is very large to ensure quality assurance of the decision database is tedious. The resource utilization required to conduct full data verification is exorbitant. This research proposes a mathematical model using deterministic statistical methods to reduce resource utilization and assures greater data quality. The proposed method validated using various data sets and volumes against man effort, CPU time, defects raised and cost. It also ensures comfortable confidence for end users to rely on the data quality for decision making.
T.N. Manjunath and Ravindra S. Hegadi, 2013. Statistical Data Quality Model for Data Migration Business Enterprise. International Journal of Soft Computing, 8: 340-351.