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Convergence-Directed, Semantic Model for Integrating Large-Scale, Dynamic, and Heterogeneous Databases

机译:集成大型,动态和异构数据库的融合导向语义模型

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摘要

Data abounds today. The ability to properly employ large amounts of data for business decisions and opportunities is critical to business success. Rarely does a single data source or database prove sufficient for a dynamic, unfolding business action. Business decision-making requires integrating data quickly and efficiently. However, the inherent differences between databases make it both time-consuming and costly to achieve a useful integration. More importantly, the storage of much of today's data has migrated away from the traditional, relational database technology and switched to NoSQL database technology. The latter provides a new set of challenges for data integration.;To address the above challenges, the semantic integration model offers a path to simplify integration across different NoSQL databases. It achieves this through an iterative, incremental integration that directly involves the non-technical business user -- the key to exploiting the business opportunity. The model contrasts current integration methods and is evaluated against a prototype that implements and tests the model with appropriate data participants. The model demonstrates an easier method to quickly review potential data integration candidates, integrate selected candidates, and maintain the alignment of the data integration with the evolving NoSQL technologies and the business opportunity itself.
机译:今天的数据比比皆是。适当地将大量数据用于业务决策和机会的能力对于业务成功至关重要。很少有单个数据源或数据库足以证明动态的,正在开展的业务活动。业务决策需要快速而有效地集成数据。但是,数据库之间的固有差异使得实现有用的集成既耗时又昂贵。更重要的是,当今许多数据的存储已从传统的关系数据库技术迁移到了NoSQL数据库技术。后者为数据集成提出了一系列新挑战。为了解决上述挑战,语义集成模型提供了简化不同NoSQL数据库之间集成的途径。它通过迭代的增量式集成实现了这一目标,该集成直接涉及非技术业务用户-这是利用商机的关键。该模型与当前的集成方法进行了对比,并针对通过适当的数据参与者实施和测试模型的原型进行了评估。该模型演示了一种更简便的方法,可以快速查看潜在的数据集成候选者,集成选定的候选者,并使数据集成与不断发展的NoSQL技术和商机本身保持一致。

著录项

  • 作者

    Hebeler, John W.;

  • 作者单位

    University of Maryland, Baltimore County.;

  • 授予单位 University of Maryland, Baltimore County.;
  • 学科 Information technology.;Information science.
  • 学位 Ph.D.
  • 年度 2017
  • 页码 184 p.
  • 总页数 184
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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