数据仓库系统正是一种基于数据分析辅助决策的方案，是数据驱动的决策支持系统的核心。
Data Warehouse system (DWS), as the core part of data-driven decision support system, is one kind of solution based on data analysis.
另外，还对DSS数据和日常操作数据进行了分析，并给出了数据驱动的决策支持系统的基本结构。
Besides, this article also analyzes DSS data and Operating data, at the name puts forward a basic construction of data driven decision support system.
从数据的观点出发，讨论了数据驱动的决策支持系统的概念及其内涵，对数据仓库、联机分析处理和数据挖掘等手段也进行了一定程度的讨论。
From the point of view of data, this article discusses the concept of data driven decision support system, its connotation, as well as data warehouse, on line Analytical Processing and data mining.
不过，实现智能化的最终本质就是进行数据驱动决策。
However, making anything smarter is ultimately about making data-driven decisions.
商业智能(Business Intelligence,BI)是对于大量数据的收集和分析，以便洞悉如何驱动战略性和策略性商业决策。
Business Intelligence (BI) is the gathering and analysis of vast amounts of data in order to gain insights that drive strategic and tactical business decisions.
总之，对于遗留集成、事务服务质量和以数据库或大型机为中心的技能集而言，数据库驱动的业务流程是强有力的体系结构设计决策。
In summary, database-driven business processes are often a strong architectural design decision for legacy integration, transactional quality of service, and database or mainframe-centric skillsets.
我想，在改进数据质量时，总是要花时间评估数据在自己的环境中如何驱动决策。
I suppose that as long as you're working on improving data quality, you might as well take the time to assess how data drives decisions in your environment.
世界每天都在从这些连接中产生越来越多的数据，每个企业都希望做出更多的可使他们更快捷的数据驱动决策。
The world is generating more and more data every day from these connections. Every business wants to make more data-driven decisions, and make them faster.
此系统是以统一数据模型驱动进行决策的。
生物医学本体论提供了必要的领域知识以驱动数据整合、信息检索、数据注释、自然语言处理和决策支持。
Biomedical ontologies provide essential domain knowledge to drive data integration, information retrieval, data annotation, natural-language processing and decision support.
我们实际的例子包括心脏的度量方式帮助产品团队做出决策，数据驱动以用户为中心的。
We include practical examples of how HEART metrics have helped product teams make decisions that are both data-driven and user-centered.
很多数据也驱动着决策过程，无论这些决策是由人还是机器来做出，如果这些数据被篡改，那些由此产生的决策结果将是灾难性的。
Much of this data also drives decision-making? By both people and machines. If that data were to be tampered with the resulting decision outcomes could be disastrous.
很多数据也驱动着决策过程，无论这些决策是由人还是机器来做出，如果这些数据被篡改，那些由此产生的决策结果将是灾难性的。
Much of this data also drives decision-making? By both people and machines. If that data were to be tampered with the resulting decision outcomes could be disastrous.
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