A Mathematical Model for Evaluation of Data Analytics Implementation Alternatives
2017 IEEE 21st International Enterprise Distributed Object Computing Workshop (EDOCW) 2017
Jānis Grabis, Rūta Pirta-Dreimane

Importance of data analytics continuously increases in modern organizations, and diversity of technologies for implementation of analytical components is also increasing. Enterprise architecture and analytical methods are helpful in selecting the most appropriate technology to ensure the right balance among strategic, development and usage considerations. This paper elaborates a mathematical model for evaluation of alternative solutions for implementation of analytical reports requested by users of enterprise applications. The alternative solutions are selected to minimize development and maintenance costs in accordance with enterprise architecture evolution principles such as centralization of common functionality and promotion of reuse. The enterprise architecture also provides input data necessary to run the model. Application of the model is demonstrated using an illustrative example highlighting some of the trade-offs faced by enterprises and systems architects. The model is intended as a decision-making guide during enterprise architecture change management.


Atslēgas vārdi
data analytics, enterprise architecture, decentralization, reuse, change management
DOI
10.1109/EDOCW.2017.21
Hipersaite
http://ieeexplore.ieee.org/document/8089835/

Grabis, J., Pirta, R. A Mathematical Model for Evaluation of Data Analytics Implementation Alternatives. No: 2017 IEEE 21st International Enterprise Distributed Object Computing Workshop (EDOCW), Kanāda, Quebec City, 10.-13. oktobris, 2017. Piscataway: IEEE, 2017, 79.-84.lpp. ISBN 978-1-5386-1569-0. e-ISBN 978-1-5386-1568-3. e-ISSN 2325-6605. Pieejams: doi:10.1109/EDOCW.2017.21

Publikācijas valoda
English (en)
RTU Zinātniskā bibliotēka.
E-pasts: uzzinas@rtu.lv; Tālr: +371 28399196