Data lake architecture: big data storage and analysis in financial banking organizations

Abstract

Data Lake is one of the dominant concepts in the era of big data. Although big data has been discussed, it still has many research challenges, especially the variety of data. It poses a huge difficulty to efficiently integrate and query the large volume of diverse data in information silos with the traditional approaches such as data warehouses. Data lakes have been proposed as a solution to this problem. This paper focuses on studying data lake architecture for banking data model based on reference to IBM’s data model. Next, this paper analyzes the role and necessity of a data lake, presents the data lake execution process and the right data lake architecture in financial banking organizations. Finally, the author discusses the benefits of data lakes in helping business departments access and analyze data across the organization, besides the technological challenges of implementing data lakes in financial and banking institutions also described in this paper.