Cloud Business Intelligence

Abstract

Using Business Intelligence in the cloud is considered a key factor for success in various fields in 2018, about 66 percent of successful organizations in BI already using cloud. 86% of Cloud BI adopters choose Amazon AWS as their first choice, 82% choose Microsoft Azure, 66% choose Google Cloud, and 36% identify IBM Bluemix as their preferred provider of cloud BI services. In recent years, both Business Intelligence and cloud computing have undergone dramatic changes and advancements. The newest capabilities that these recent developments bring forth are introduced. In this paper the latest technologies in the field of Cloud (SaaS) BI is introduced. The paper shows also that many of the current problems in Cloud (SaaS) BI can be solved by enhance the performance and increase the use and acceptance of this technology. Many of the key characteristics of Business Intelligence systems tend to complement those of cloud computing systems and vice versa. Therefore, when integrated properly, these two technologies can be made to strengthen each other's advantages and eliminate each other's weaknesses.

Cognizant computing + transformative marketing: an intelligent solution for sustainable business development

“…Synchronizing manually executed, physical processes: Within the context of technology-enabled firms and business processes, business process management systems integrate with digital solutions that are often powered by mobile applications to automate physical processes that would otherwise have needed to be executed manually by business stakeholders (employees, vendors and customers) in operational circumstances. CC allows data to be synchronized across these processes with insights (ElMalah and Nasr, 2019) that relevantly support the goals of management in adding and preserving value for all participating stakeholders.…”

“…This is made possible by two foundational emerging technologies (Awodele et al , 2014): the Internet of Things (IoT), which pervasively accumulates client/user data from across various interconnected sources, interfaces, devices, systems and applications (Sisinni et al , 2018), and cloud computing , which consolidates and provisions this (big) data, so that it can be accessed, processed, manipulated and analysed ubiquitously to avail business intelligence on-demand (ElMalah and Nasr, 2019). Both these technologies provide the backbones for aggregating customer/client data in this manner to be applied for various data-driven utilities towards improving business processes, enhancing administrative tasks and powering development.…”

The Future of Internet of Things for Anomalies Detection using Thermography

“…Utilizing fog computing platform minimize the vulgarity demand and reduce the relevant medical and treatment costs. Fog computing have developing applications into other frameworks such as geo-spatial data associated with many medical and healthcare problems [25,26]. The Fog computer improves the every competence by allowing and offering computing close the edge devices.…”

Modeling of the process of providing telecommunication services in cloud systems

“…This is a convenient way to test intended solutions to problems, and avoid interfering with active objects, which can lead to crashes, data loss, and system corruption. In addition, the use of simulation packages greatly facilitates the debugging and evaluation of resource management algorithms, allowing them to be carried out more quickly and efficiently [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15].…”

“…And the use of cloud services is one of the promising tasks, the solution and integration of which with existing systems and equipment will significantly increase the efficiency of the devices involved in favor of expanding the range of services provided both in relation to telecommunication networks within the technological process and in the business management of the entire company. And taking into account the currently ongoing global project for the organization of a multiservice data transmission network and the widespread modernization of individual regions for the organization of a high-speed transport data transmission network, it will allow modeling and preliminary assessment of the effectiveness of the services provided in such communication networks already at the current stage [2,9,12].…”