APA 6th Edition Rutz, D., Nelakanti, T. i Rahman, N. (2012). Practical Implications of Real Time Business Intelligence. Journal of computing and information technology, 20 (4), 257-264. https://doi.org/10.2498/cit.1002081
MLA 8th Edition Rutz, Dale, et al. "Practical Implications of Real Time Business Intelligence." Journal of computing and information technology, vol. 20, br. 4, 2012, str. 257-264. https://doi.org/10.2498/cit.1002081. Citirano 27.02.2021.
Chicago 17th Edition Rutz, Dale, Tara Nelakanti i Nayem Rahman. "Practical Implications of Real Time Business Intelligence." Journal of computing and information technology 20, br. 4 (2012): 257-264. https://doi.org/10.2498/cit.1002081
Harvard Rutz, D., Nelakanti, T., i Rahman, N. (2012). 'Practical Implications of Real Time Business Intelligence', Journal of computing and information technology, 20(4), str. 257-264. https://doi.org/10.2498/cit.1002081
Vancouver Rutz D, Nelakanti T, Rahman N. Practical Implications of Real Time Business Intelligence. Journal of computing and information technology [Internet]. 2012 [pristupljeno 27.02.2021.];20(4):257-264. https://doi.org/10.2498/cit.1002081
IEEE D. Rutz, T. Nelakanti i N. Rahman, "Practical Implications of Real Time Business Intelligence", Journal of computing and information technology, vol.20, br. 4, str. 257-264, 2012. [Online]. https://doi.org/10.2498/cit.1002081
Sažetak The primary purpose of business intelligence is to improve the quality of decisions while decreasing the time it takes to make them. Because focus is required on internal as well as external factors, it is critical to decrease data latency, improve report performance and decrease systems resource consumption. This article will discuss the successful implementation of a BI reporting project directly against an OLTP planning solver. The planning solver imports data concerning supply, demand, capacity, bill of materials, inventory and the like. It then uses linear programming to determine the correct product mix to produce at various factories worldwide. The article discusses the challenges faced and a working model in which real-time BI was achieved by providing data to a separate BI server in an innovativeway resulting in decreased latency, reduced resource consumption and improved performance. We demonstrated an alternative approach to hosting data for the BI application separately by loading BI and solver databases at the same time, resulting in faster access to information.