Building Data Warehouse and Dashboard of Church Congregation Data

R. Irawan, B. Susanto, Yuan Lukito
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引用次数: 1

Abstract

A data warehouse is essential for an organization to process and analyze data coming from the organization. Hence, a data warehouse together with a dashboard to visualize the processed data are built to accommodate the need of the church administrator to analyze a large set of church congregation data. The data warehouse is built using the Kimball principle. This Kimball principle emphasizes the implementation of a dimensional model in the data warehouse, not a relational model used in a regular transactional database. An ETL process that contains extract, transform and load processes is used to retrieve all data from the regular transactional database and transform the data so the data can be loaded into the data warehouse. A dashboard is then built to visualize the data from the data warehouse so the users can view the processed data easily. Users can also export the processed data into an excel file that can be downloaded from the dashboard. A web service is built to get data from the data warehouse and return it to the dashboard.
建立数据仓库和教会会众数据仪表板
数据仓库对于组织处理和分析来自组织的数据至关重要。因此,为了满足教会管理员分析大量教会聚会数据的需要,我们构建了一个数据仓库和一个仪表板,用于可视化处理后的数据。数据仓库是使用Kimball原理构建的。这个Kimball原则强调在数据仓库中实现维度模型,而不是在常规事务性数据库中使用的关系模型。包含提取、转换和加载过程的ETL流程用于从常规事务性数据库检索所有数据并转换数据,以便将数据加载到数据仓库中。然后构建一个仪表板来可视化来自数据仓库的数据,以便用户可以轻松地查看处理过的数据。用户还可以将处理后的数据导出为excel文件,然后从仪表板下载。构建web服务用于从数据仓库获取数据并将其返回到仪表板。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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