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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References
Conn, S.S.: OLTP and OLAP data integration: a review of feasible implementation methods and architectures for real time data analysis. In: Proceedings of the SoutheastCon, pp. 515–520. IEEE (2005)
Das, K.K., Fratkin, E., Gorajek, A.: Massively Parallel In-Database Predictions using PMML. In: PMML 2011 (2011)
ALzain, M.A., Pardede, E.: Using Multi Shares for Ensuring Privacy in Database-as-a-Service. In: System Sciences (HICSS), pp. 1–9 (2011)
Davidson, G.S., Boyack, K.W., Zacharski, R.A., Helmreich, S.C., Cowie, J.R.: Data-Centric Computing with the Netezza Architecture. SANDIA REPORT, SAND2006-1853, Unlimited Release, Printed (April 2006)
Chen, H., Chiang, R.H.L., Storey, V.C.: Business intelligence and analytics: From big data to big impact. MIS Quarterly (11), 1–24 (2012)
Revolutions, R users: Be counted in Rexer’s, Data Miner Survey (January 30, 2013)
Hornick, M.: Quick! Swap those models – I’ve got a better one (August 12, 2013)
Oracle White Paper, Big Data Analytics - Advanced Analytics in Oracle Database (March 2013)
Oracle White Paper, Bringing R to the Enterprise - A Familiar R Environment with Enterprise-Caliber Performance, Scalability, and Security (May 2013)
Hornick, M.: Senior Manager, Development, Session 2: Oracle R Enterprise 1.3 Transparency Layer (2012)
SAS Documentation, SAS® 9.4 In-Database Products User’s Guide Second Edition SAS (2013)
Neugebauer, A.: SYBASE IQ 15 In-Database Analytics Option
Urbanek, S.: Rserve - A Fast Way to Provide R Functionality to Applications, Proceedings of the 3rd International Workshop on Distributed Statistical Computing (DSC 2003), March 20-22 (2003)
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© 2014 Springer International Publishing Switzerland
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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: Miao, D., Pedrycz, W., Ślȩzak, D., Peters, G., Hu, Q., Wang, R. (eds) Rough Sets and Knowledge Technology. RSKT 2014. Lecture Notes in Computer Science(), vol 8818. Springer, Cham. https://doi.org/10.1007/978-3-319-11740-9_35
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DOI: https://doi.org/10.1007/978-3-319-11740-9_35
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-11739-3
Online ISBN: 978-3-319-11740-9
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