使用混合OLAP多维数据集分配和管理教学工作量的交互式框架

W. Haque
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引用次数: 0

摘要

教学工作量分配是所有学术机构必不可少的年度仪式。根据结构和复杂程度的不同,对于负责资源分配的部门主管和行政院长来说,这可能是一个痛苦的过程。我们提出了一个框架,该框架使用商业智能技术在协作环境中允许异步数据输入、分析和报告,以协助决策过程。首先,第一层管理员使用交互式web表单与教员协商完成工作负载分配,将数据推送到底层数据库或多维数据集,呈现报告,并自动生成备忘录。负责审批的院长能够从几个方面审查信息,并就任务做出明智的决定。历史数据仍可用于未来几年的趋势和分析。除了从流程透明性中获益之外,该框架还利用OLAP多维数据集和关系数据存储来实现最佳性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Interactive Framework to Allocate and Manage Teaching Workload using Hybrid OLAP Cubes
Assignment of teaching workload is an essential annual ritual in all academic institutions. Depending upon the structure and complexity, it can be a painful process for department heads and administrative deans who are responsible for resource allocation. We present a framework which uses business intelligence techniques to allow asynchronous data entry, analysis and reporting in a collaborative environment to assist with the decision-making process. To begin, the first-tier administrators make workload assignments in consultation with faculty using interactive web forms, data is pushed to the underlying database or cube, reports are rendered, and memos are auto-generated. Deans responsible for approval are able to review the information along several dimensions and make informed decisions regarding the assignments. Historical data remains available for future years for trends and analysis. Besides achieving the benefits from transparency of the process, the framework exploits both OLAP cubes and relational data stores for optimum performance.
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