面向文档数据库的数据仓库模式提取

A. Istiqamah, Kemas Wiharja
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引用次数: 1

摘要

数据仓库是一种非常有名的解决方案,用于分析来自异构源的业务数据。不幸的是,数据仓库只能分析结构化数据。然而,如今,由于社交媒体的普及和在网络上创建数据的便利性,我们正在经历非结构化数据的洪流。因此,我们需要一种方法,可以将非结构化数据“结构化”为结构化数据,从而可以由数据仓库处理。为此,我们提出了一种使用谷歌云平台的模式提取方法,该方法将从非结构化数据创建模式。根据我们的实验,我们的方法成功地从非结构化数据生成模式。据我们所知,我们是第一个使用谷歌云平台提取模式的公司。我们还证明了我们的方法可以帮助数据库开发人员更好地理解非结构化数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
a Schema Extraction of Document-Oriented Database for Data Warehouse
The data warehouse is a very famous solution for analyzing business data from heterogeneous sources. Unfortunately, a data warehouse only can analyze structured data. Whereas, nowadays, thanks to the popularity of social media and the ease of creating data on the web, we are experiencing a flood of unstructured data. Therefore, we need an approach that can "structure" the unstructured data into structured data that can be processed by the data warehouse. To do this, we propose a schema extraction approach using Google Cloud Platform that will create a schema from unstructured data. Based on our experiment, our approach successfully produces a schema from unstructured data. To the best of our knowledge, we are the first in using Google Cloud Platform for extracting a schema. We also prove that our approach helps the database developer to understand the unstructured data better.
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