Robust analysis and optimization of a novel efficient quality assurance model in data warehousing. (March 2019)

• Record Type: Journal Article
• Authors: Amuthabala, P.; Santhosh, R.
• Is Part Of: Computers & electrical engineering. Volume 74(2019)
• Page Start: 233
• Page End: 244
• Publication Date: 2019-03
• Subjects: Data warehouse -- Distributed -- Data complexity -- Data quality -- Quality assurance -- Optimization -- Machine learning; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2019.02.003
• Languages: English
• ISSNs: 0045-7906

Abstract

Abstract: The significance of distributed data warehouses is to initiate the proliferation of various analytical applications. However, with the increase of ubiquitous devices, it is likely that massive volumes of data will be generated, which poses further problems based on the degradation of data quality. The practical reasons for the degradation of data quality in distributed warehouses are identified as heterogeneous data, uncertain inferior data which further affect predictions. The proposed system presents an integrated optimization model to address all the quality degradation problems and to provide a better computational model which effectively incorporates a higher degree of quality assurance. An analytical methodology is adopted in order to develop the proposed quality assurance model for distributed data warehouses.