A dynamic and user-centric data cleaning system for Watson Analytics

Watson Analytics 的动态且以用户为中心的数据清理系统

• 批准号: 490788-2015
• 负责人: Chiang, FeiYen
• 金额: $ 4.95万
• 依托单位: McMaster University
• 依托单位国家: 加拿大
• 项目类别: Collaborative Research and Development Grants
• 财政年份: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=601540
• 关键词: dynamic; user; centric; data; cleaning

Poor data quality is a serious and costly problem affecting organizations across all industries. Real data is often dirty, containing missing, erroneous, incomplete, and duplicate values. It is estimated that poor data quality cost organizations between 15% and 25% of their operating budget. Existing data cleaning solutions focus on identifying inconsistencies that do not conform to prescribed data formats assuming the data remains relatively static. As modern applications move towards more dynamic search and analytics, new data quality solutions that support dynamic and adaptive data cleaning are needed.

数据质量差是影响所有行业组织的一个严重且代价高昂的问题。真实数据通常是脏的，包含丢失的、错误的、不完整的和重复的值。据估计，糟糕的数据质量使组织损失了15%到25%的运营预算。现有的数据清理解决方案侧重于识别不符合规定数据格式的不一致性，假设数据保持相对静态。随着现代应用程序转向更动态的搜索和分析，需要支持动态和自适应数据清理的新数据质量解决方案。