Effective and Efficient Data Quality Management for Data Lakes

该项目旨在通过创新和明智地使用数据库和人工智能技术来提高数据湖中数据的质量和完整性。为了实现这一目标，我们将在数据摄取过程中开发知识增强的错误纠正，灵活高效的数据探索，以及异构容忍的可扩展数据集成解决方案。其意义在于整合数据库和人工智能领域的技术，为数据湖中的挑战性问题提供有效的解决方案。该项目的成果将为这一前沿领域提供新的知识，并为建立在数据湖上的所有应用程序提供额外的价值和直接的好处。

This project aims to enhance the quality and completeness for data in data lakes by innovative and judicious use of Database and Artificial Intelligence techniques. To achieve the aim, we will develop knowledge-enhanced error correction during data ingestion, flexible and efficient data exploration, and heterogeneity-tolerant scalable data integration solutions. Its significance lies in integrating techniques from both database and artificial intelligence areas to deliver effective solutions for challenging problems in data lakes. The outcome of this project will provide new knowledge in this cutting-edge domain, and provide additional value and immediate benefits to all applications built upon data lakes.