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What Role Does a Data Warehouse Play in A Service-Oriented Architecture?

机译:数据仓库在面向服务的体系结构中扮演什么角色?

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Description of the Material Organizations have long struggled with providing integration, interoperability and data exchange among a variety of disparate databases across the enterprise. Many organizations are adopting service-oriented architectures (SOA) to provide both application and data integration services. Incorporating data warehousing into an overall service-oriented architecture is critical for enabling integrated business intelligence. Application Business intelligence architectures focus on delivering data from source systems to data warehouses and then to data marts for reporting and analytical applications. They have typically used ETL to move data, and more recently, EAI. SOA brings the promise of using an umbrella approach for not just batch data movement, but also for real-time application and data integration. This paper describes how data warehousing fits into a service-oriented architecture, some of the common challenges that it addresses and what the combined architecture looks like. Additionally, this paper takes a look at a common business scenario utilizing Data Warehousing within a service-oriented architecture. Results, Observations and Conclusions Successful business process management and access to direct transactional business intelligence are two of the main benefits resulting from the capture of timely, accurate data at the source. Creating business intelligence that performs efficiently and provides strong corporate memory requires incorporation of data warehousing into the overall serviceoriented architecture model. Undertaken correctly, SOA can supplement existing technologies to deliver data and process driven business intelligence. Significance of Subject Matter The challenges of lack of data standards, "silos" of information, and lack of a common integration framework make the SOA promise of easier data and application integration sound very appealing. Many oil and gas companies have started implementing SOAs within their enterprises. With business intelligence solutions continuing to be a top focus for Oil & Gas IT leaders, informal surveys of this same group have found that many lack an understanding of the composite view of SOA and BI.
机译:物料描述组织一直在努力在整个企业的各种不同数据库之间提供集成,互操作性和数据交换。许多组织正在采用面向服务的体系结构(SOA)来提供应用程序和数据集成服务。将数据仓库整合到整个面向服务的体系结构中对于实现集成的商业智能至关重要。应用程序商业智能体系结构专注于将数据从源系统传递到数据仓库,然后传递到数据集市以进行报告和分析应用程序。他们通常使用ETL来移动数据,最近使用EAI来移动数据。 SOA带来了使用伞式方法的希望,不仅可以用于批处理数据移动,还可以用于实时应用程序和数据集成。本文描述了数据仓库如何适应面向服务的体系结构,它解决的一些常见挑战以及组合体系结构的外观。此外,本文研究了在面向服务的体系结构中利用数据仓库的常见业务场景。结果,观察结果和结论成功的业务流程管理和获得直接交易业务智能的能力是从源头获取及时,准确的数据所带来的两个主要好处。要创建有效执行并提供强大的公司内存的商业智能,需要将数据仓库纳入整个面向服务的体系结构模型中。正确地采用SOA可以补充现有技术,以提供数据和流程驱动的商业智能。主题的重要性缺乏数据标准,信息“孤岛”和缺乏通用的集成框架的挑战使SOA承诺更容易进行数据和应用程序集成听起来非常有吸引力。许多石油和天然气公司已开始在企业内部实施SOA。随着商业智能解决方案继续成为油气IT领导者的头等大事,对该小组的非正式调查发现,许多人对SOA和BI的综合视图缺乏了解。

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