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Big Data Quality Assurance Model and Method

Low-quality data can cause a lot of property and business losses. Data quality management aims to improve data availability by discovering data semantics rules, automatically locating and fixing data errors. We develop a data availability platform based on the original data quality theory. It features automatic management, and forms a positive cycle of interaction between data and the platform, promoting high-quality applications of data production factors in various industries, and leading a usable development of global data.

Research Areas

Aiming at the five key data quality dimensions-—consistency, accuracy, completeness, timeliness and identity of entities—the research works on a presentation model and description language of data rules, data rule auto-mining algorithm, reasoning system and rules correctness detection, data error auto-detection and positioning, as well as data restoration theory and other key technologies.

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