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首页> 外文期刊>Procedia Computer Science >Development of a University Financial Data Warehouse and its Visualization Tool
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Development of a University Financial Data Warehouse and its Visualization Tool

机译：高校财务数据仓库的开发及其可视化工具

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摘要

In today's data-driven world, organizations which make use of the transactional data they have accumulated over time to come up with a more realistic picture of their operations can make more informed decisions towards attaining their goals and interests. However, due to the huge volumes of these accumulated transactional data, they cannot just be easily and readily used for reporting and analysis purposes. With this, a data warehouse is needed to store these accumulated data obtained from different sources within an organization where other decision-support applications can be built on to guide management decisions. In this study, a financial data warehouse was developed with a multidimensional construct that splits time, finance unit, account, and time dimensions, which is updated periodically with the accumulated transactional data sourced from a financial database of a university, and accessible via a Representational State Transfer application programming interface (REST API). To demonstrate the API's functionalities, we have created a data visualization tool which we integrated into our university web portal and subjected it to usability testing by its target end-users. It was shown that most of the respondents find the tool useful. Also, a query performance test was conducted comparing the execution of certain queries on the source transactional database and on the data warehouse. Result showed that the query time was greatly reduced by an average of over 50% when these queries were executed on the latter.
机译：在当今数据驱动的世界中，组织可以利用随着时间推移而积累的交易数据来更真实地了解其运营情况，从而可以做出更明智的决策，以实现其目标和利益。但是，由于这些累积的交易数据量巨大，因此不能轻松方便地将其用于报告和分析目的。因此，需要一个数据仓库来存储从组织内的不同来源获得的这些累积数据，在该组织上可以构建其他决策支持应用程序来指导管理决策。在本研究中，开发了一种财务数据仓库，它具有多维结构，该结构可以拆分时间，财务单位，科目和时间维度，并定期使用来自大学财务数据库的累积交易数据进行更新，并可以通过代表机构进行访问状态转移应用程序编程接口（REST API）。为了演示API的功能，我们创建了一个数据可视化工具，将其集成到我们的大学Web门户中，并对其目标最终用户进行了可用性测试。结果表明，大多数受访者认为该工具很有用。此外，还进行了查询性能测试，比较了源事务数据库和数据仓库上某些查询的执行情况。结果表明，对后者执行查询时，查询时间平均平均减少了50％以上。

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