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Agile Development in Data Warehousing

机译:数据仓库中的敏捷开发

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Traditional data warehouse projects follow a waterfall development model in which the project goes through distinct phases such as requirements gathering, design, development, testing, deployment, and stabilization. However, both business requirements and technology are complex in nature and the waterfall model can take six to nine months to fully implement a solution; by then business as well as technology has often changed considerably. The result is disappointed stakeholders and frustrated development teams. Agile development implements projects in an iterative fashion. Also known as the sixty percent solution, the agile approach seeks to deliver more than half of the user requirements in the initial release, with refinements coming in a series of subsequent releases which are scheduled at regular intervals. An agile data warehousing approach greatly increases the likelihood of successful implementation on time and within budget. This article discusses agile development methodologies in data warehousing and business intelligence, implications of the agile methodology, managing changes in data warehouses given frequent change in business intelligence (BI) requirements, and demonstrates the impact of agility on the business.
机译:传统的数据仓库项目遵循瀑布式开发模型,在该模型中,项目经历了不同的阶段,例如需求收集,设计,开发,测试,部署和稳定。但是,业务需求和技术本质上都是复杂的,瀑布模型可能需要六至九个月才能完全实施解决方案。到那时,商业和技术通常已经发生了很大的变化。结果是使利益相关者感到失望,并使开发团队感到沮丧。敏捷开发以迭代方式实施项目。敏捷方法也被称为百分之六十的解决方案,旨在在初始版本中交付一半以上的用户需求,并在一系列定期发布的后续版本中进行改进。敏捷的数据仓库方法大大增加了按时且在预算范围内成功实施的可能性。本文讨论了数据仓库和商业智能中的敏捷开发方法论,敏捷方法论的含义,在频繁更改商业智能(BI)要求的情况下管理数据仓库中的变化,并论证了敏捷性对业务的影响。

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