An approach for in-database scoring of R models on DB2 for z/OS

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Abstract

Business Analytics is comprehensively used in many enterprises with large scale of data from databases and analytics tools like R. However, isolation between database and data analysis tool increases the complexity of business analytics, for it will cause redundant steps such as data migration and engender latent security problem. In this paper, we propose an in-database scoring mechanism, enabling application developers to consume business analytics technology. We also validate the feasibility of the mechanism using R engine and IBM DB2 for z/OS. The result evinces that in-database scoring technique can be applicable to relational databases, largely simplify the process of business analytics, and more importantly, keep data governance privacy, performance and ownership.

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APA

Xian, Y., Huang, J., Shuf, Y., Fuh, G., & Gao, Z. (2014). An approach for in-database scoring of R models on DB2 for z/OS. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8818, pp. 376–385). Springer Verlag. https://doi.org/10.1007/978-3-319-11740-9_35

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