A Granular Computing Methodology to Improve Record Quality for Master Data Management

提高主数据管理记录质量的精细计算方法

• 批准号: 462980-2014
• 负责人: Pedrycz, Witold
• 金额: $ 10.76万
• 依托单位: University of Alberta
• 依托单位国家: 加拿大
• 项目类别: Strategic Projects - Group
• 财政年份: 2014
• 资助国家: 加拿大
• 起止时间: 2014-01-01 至 2015-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=558183
• 关键词: Granular; Computing; Methodology; Improve; Record

Master Data Management (MDM) is a corporate process that ensures the accuracy, uniformity, proper stewardship, privacy, semantic consistency, and accountability of a company's master data assets. Master data is the consistent set of business identifiers and attributes that describe the core entities of a company. A key aspect of a company's MDM solution is the creation of a "golden record" for every client of interest. These golden records are linked, synchronized, and aggregated using sets of heterogeneous information across distributed data repositories. As storage costs decrease and big data technologies mature, companies can store more complex, voluminous, and varied (schematized, semi-structured, unstructured, social media, and so on) identifiers and attributes.

主数据管理（MDM）是一个企业流程，可确保公司主数据资产的准确性、一致性、适当的管理、隐私性、语义一致性和可问责性。主数据是描述公司核心实体的业务标识符和属性的一致集合。公司MDM解决方案的一个关键方面是为每个感兴趣的客户机创建“黄金记录”。这些黄金记录使用跨分布式数据存储库的异构信息集进行链接、同步和聚合。随着存储成本的降低和大数据技术的成熟，公司可以存储更复杂、更大、更多样化（模式化、半结构化、非结构化、社交媒体等）的标识符和属性。