Abstract
Data analytics is an ever-growing field which provides insights, predictions and patterns from raw data. The outcome of analytics is greatly affected by the quality of input data on which the analytics is done. This paper explores the design of a quality-aware data capture system, which uses Data Mining Techniques and algorithms, specifically a decision-tree based approach for data validation and verification, with an objective of identifying data quality issues right at a stage when data enters the system by providing appropriate feedback through a carefully designed user-interface.
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This work was supported by a grant from Evive Software Analytics Pvt. Ltd.
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Mehta, R.V.K., Verma, S. (2017). Design of a Quality-Aware Data Capture System. In: Tan, Y., Takagi, H., Shi, Y. (eds) Data Mining and Big Data. DMBD 2017. Lecture Notes in Computer Science(), vol 10387. Springer, Cham. https://doi.org/10.1007/978-3-319-61845-6_28
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DOI: https://doi.org/10.1007/978-3-319-61845-6_28
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