数据仓库中不同提取转换和加载工具的比较

2018 International Conference on Innovations in Science, Engineering and Technology (ICISET) Pub Date : 2018-10-01 DOI:10.1109/ICISET.2018.8745574

Md. Badiuzzaman Biplob, Galib Ahasan Sheraji, S. I. Khan

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引用次数: 4

摘要

数据仓库(DW)是支持存储和分析历史数据的数据库实现。DWs的关键组件被称为提取、转换和加载(ETL)。因为错误或误导性的数据可能会产生错误的结果。数据仓库需要合适的ETL工具来提高数据质量。在数据仓库中，ETL工具的选择是一个难题，也是一个重要问题。本文首先简要介绍了ETL过程，并比较了ETL工具的特点。在本文中，我们比较了现有的ETL工具，以选择在不同情况下的最佳选择。从当前的工业市场中，我们收集了来自行业专业人士的反馈，并将其记录下来，以建立数据仓库的相关性。我们实施了现有的流行ETL工具，比较它们的优缺点，从中选择最佳工具用于孟加拉国国家卫生数据仓库。

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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Comparison of Different Extraction Transformation and Loading Tools for Data Warehousing

Data Warehouses (DW) are database implementations that support the storage and analysis of historical data. The key components of DWs are known as Extraction, Transformation, and Loading (ETL). Since wrong or misleading data may deliver the wrong results. Suitable ETL Tools are necessary for a DW to enhance data quality. The choice of ETL tools is difficult as well as important issue in data warehousing. This paper first describes the ETL procedure in brief and compare the features of the ETL tools. In this paper, we have compared the existing ETL tools to choose the best option in different situations. From a current industrial market, we collected feedback from the industry professional and documented it to establish the relevance of the data warehouse. We have implemented the available popular ETL tools to compare their strengths and weaknesses to choose the best among them for National Health Data Warehouse of Bangladesh.

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2018 International Conference on Innovations in Science, Engineering and Technology (ICISET)

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