用OLAP和OLAP解决数据仓库中的调度问题

Himanshi Kataria, A. Garg
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引用次数: 0

摘要

仓库和数据集市中的数据由一个或多个仓库服务器存储和管理,这些服务器将数据的多维视图呈现给各种前端工具:查询工具、报表编写器、分析工具和数据挖掘工具。最后,还有一个用于存储和管理元数据的存储库,以及用于监视和管理仓储系统的工具。业务数据库由于所发生的事务每天都要进行频繁的更改。假设业务管理人员想要分析任何数据(如产品、供应商或任何消费者数据)的先前反馈,那么执行人员将没有可用的数据来分析,因为先前的数据已经由于事务而更新。数据仓库帮助业务主管组织、分析和使用他们的数据进行决策。数据仓库是企业管理计划-执行-评估“闭环”反馈系统的唯一组成部分。数据仓库广泛应用于以下领域:金融服务。银行服务。消费品。零售行业。生产控制。
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Solving Scheduling Problem in Data Ware House Using OLAP and OLAP
Data in the warehouse and data marts is stored and managed by one or more warehouse servers, which present multidimensional views of data to a variety of front end tools: query tools, report writers, analysis tools, and data mining tools. Finally, there is a repository for storing and managing metadata, and tools for monitoring and administering the warehousing system.  An operational database undergoes frequent changes on a daily basis on account of transactions that taken area. Think a business management wants to analyze previous feedback on any data such as a product, a supplier, or any consumer data, then executive will had no data available to analyze because  previous data has been updated due to transactions. A data warehouse helps business executives to organize, analyze, & use their data for decision making. A data warehouse serves as a sole part of a plan-execute-assess "closed-loop" feedback system for  enterprise management. Data warehouses are widely used in  following fields: Financial services. Banking services. Consumer goods. Retail sectors. Controlled manufacturing.
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