Query-Driven Approach (QDA) that systematically exploits selection queries to reduce the data cleaning overhead

Dr. Yamarthi Narasimha Rao, Alagadri Sreekanth, Thumu Venkata Ajay Kumar, Challa Jaswanth Sai, Nallagorla Ajay, Sai Venkata Sumanth Katragadda
Page No: 1-07
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This paper explores "on-the-fly" data cleaning in the context of a user query. A novel QueryDriven Approach (QDA) is developed that performs a minimal number of cleaning steps that are only necessary to answer a given selection query correctly. The comprehensive empirical evaluation of the proposed approach demonstrates its significant advantage in terms of efficiency over traditional techniques for query-driven applications.The significance of data quality research is motivated by the observation that the of data-driven technologies such as decision support tools, data exploration,analysis, and scientific discovery tools is closely tied to the quality of data to which such techniques are applied. It is well recognized that the outcome of the analysis is only as good as the data on which the analysis is performed. That is why today organizations spend a substantial percentage of their budgets on cleaning tasks such as removing duplicates,correcting errors, and lling missing values, to improve data quality prior to pushing data through the analysis pipeline.Given the critical importance of the problem, many efforts, in both industry and academia, have explored systematic approaches to addressing the cleaning challenges.

Citations

APA: Dr. Yamarthi Narasimha Rao, Alagadri Sreekanth, Thumu Venkata Ajay Kumar, Challa Jaswanth Sai, Nallagorla Ajay, Sai Venkata Sumanth Katragadda (2025). Query-Driven Approach (QDA) that systematically exploits selection queries to reduce the data cleaning overhead. DOI: 10.86493/VEREDAS.2024/V14I1/01

AMA: Dr. Yamarthi Narasimha Rao, Alagadri Sreekanth, Thumu Venkata Ajay Kumar, Challa Jaswanth Sai, Nallagorla Ajay, Sai Venkata Sumanth Katragadda. Query-Driven Approach (QDA) that systematically exploits selection queries to reduce the data cleaning overhead. 2025. DOI: 10.86493/VEREDAS.2024/V14I1/01

Chicago: Dr. Yamarthi Narasimha Rao, Alagadri Sreekanth, Thumu Venkata Ajay Kumar, Challa Jaswanth Sai, Nallagorla Ajay, Sai Venkata Sumanth Katragadda. "Query-Driven Approach (QDA) that systematically exploits selection queries to reduce the data cleaning overhead." Published 2025. DOI: 10.86493/VEREDAS.2024/V14I1/01

IEEE: Dr. Yamarthi Narasimha Rao, Alagadri Sreekanth, Thumu Venkata Ajay Kumar, Challa Jaswanth Sai, Nallagorla Ajay, Sai Venkata Sumanth Katragadda, "Query-Driven Approach (QDA) that systematically exploits selection queries to reduce the data cleaning overhead," 2025, DOI: 10.86493/VEREDAS.2024/V14I1/01

ISNAD: Dr. Yamarthi Narasimha Rao, Alagadri Sreekanth, Thumu Venkata Ajay Kumar, Challa Jaswanth Sai, Nallagorla Ajay, Sai Venkata Sumanth Katragadda. "Query-Driven Approach (QDA) that systematically exploits selection queries to reduce the data cleaning overhead." DOI: 10.86493/VEREDAS.2024/V14I1/01

MLA: Dr. Yamarthi Narasimha Rao, Alagadri Sreekanth, Thumu Venkata Ajay Kumar, Challa Jaswanth Sai, Nallagorla Ajay, Sai Venkata Sumanth Katragadda. "Query-Driven Approach (QDA) that systematically exploits selection queries to reduce the data cleaning overhead." 2025, DOI: 10.86493/VEREDAS.2024/V14I1/01