对银行业标准进行评估，以确定其是否适合构建基于大数据的银行业数据湖数据模型

2020 IEEE International Conference on Technology, Engineering, Management for Societal impact using Marketing, Entrepreneurship and Talent (TEMSMET) Pub Date : 2020-12-10 DOI:10.1109/TEMSMET51618.2020.9557578

N. B. Satyendra, Neeraja K. Swami, Priyanka V. Bhailume

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引用次数: 0

摘要

为银行建立数据湖是为了满足银行的报告和分析需求。因此，Data Lake的设计目的是提供决策查询和结果，这些查询和结果将根据银行需求进行分析。银行的数据湖本质上是OLAP。仅仅复制源系统模式并不能转化为有效的数据湖。它需要对数据进行重组，并创建适当的数据模型，以满足所需的银行需求。银行界最著名的三个标准是BIAN、ISO 20022和FIBO。在本文中，我们探讨了这些标准对于构建数据模型的适用性，这些模型可以被银行用于其基于大数据的数据湖。

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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Evaluation of Banking Standards to ascertain their suitability for building Data Models for Big data based Data Lake for Banking Domain

Data Lakes for banks are built to take care of the reporting and Analytics needs of the banks. Hence Data Lake is designed to provide the decision-making queries and results that are analyzed for Banking needs. Data Lakes of banks are OLAP in nature. A mere duplication of source system schema doesn’t translate into an effective Data Lake. It requires a restructuring of data and creating appropriate data models to suit the required Banking needs. The three notable standards in Banking are BIAN, ISO 20022 and FIBO. In this paper, we explore the suitability of these standards for building the data models that can be used by Banks for its Big data based Data Lake.

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2020 IEEE International Conference on Technology, Engineering, Management for Societal impact using Marketing, Entrepreneurship and Talent (TEMSMET)

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