Data Lake Architecture for a Banking Data Model
Keywords:
Banking, Data Lake, Data Warehouse, Big DataAbstract
Industry models provide an excellent opportunity to accelerate development based on best practices and standards which are introduced in industry models. One such model is a banking model for data warehouse. Traditional data warehousing technologies are based on relational database engines, data consistency and high normalization, but in more recent period data lake has become more and more interesting. Main advantages of the data lake landscape are commodity hardware, open source technologies with cost-free software and elastic scalability. In this paper we will present how data lake can be used in addition to data warehouse. The aim of the paper is presenting a possible data lake architecture for the banking industry model which is considered in a certain international banking company.
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References
Awadallah, A., Graham, D. (2011), “Hadoop and the Data Warehouse: When to Use Which”, available at: marketing.teradata.com/When-to-Use-Hadoop (05 April 2019).
O’Brien, H. (2015), Agile Project Management: A Quick Start Beginner’s Guide To Mastering Agile Project Management, CreateSpace Publishing.
Clifford, A., Murphy, D., Fritzsimons, G., Meehan, P., O’Suilleabhain, R., Abed, S. (2012), Best Practices, Transforming IBM Industry Models into a production data warehouse.
IBM (2006), IBM Industry Models for Financial Services, The Information FrameWork (IFW) Overview.
Documentation from the project (International banking company).
