Current work presents new approach for designing business intelligence solutions. In the era of big data, former and robust analytical concepts and utilities needs to adopt themselves to changed market circumstances. Main focus of the work is to address acceleration of building process of a “data-centric” business intelligence solution on one side, and also prepare business intelligence solutions for big data utilization. Research is addressing following goals: (a) reduce time spent during business intelligence solution designing phase; (b) achieve flexibility of business intelligence solution by removing problems with adding new data sources; (c) prepare business intelligence solution for utilization of big data concepts. Research proposes extension of existing Extract, Load and Transform (ELT) approach to the new one Extract, Load, Transform and Analyse (ELTA)

Nowadays enterprises demand mobility and flexibility of their employees as inevitable success factors. Integrating mobile devices like smartphones and tablets into an enterprise gives employees possibilities to work more productively. However, integrating mobile devices and applications has also brought new security challenges and risks. Despite all advantages of mobility, many organizations continue to avoid it due to security issues. Mobile devices are exposed to a wide range of threats that have to be countered. Simply porting information security standards from workstations, notebooks, and server domains to mobile devices is unlikely to be effective. Thus, from enterprise point of view, security levels are not clear on mobile devices. Generally, a high level of security might be reached on mobile devices by setting a high level of restrictions. On the other hand, this might minimize user acceptance and satisfaction factors. In this research, risk analysis with focus on mobile devices is conducted and a framework for designing secure mobile enterprise applications (MEAs) is developed and presented along with step-by-step guidelines. This research mainly supports enterprises in decision-making process during designing MEAs and helping developers to understand the mobile security issues and classify MEAs into security levels. Moreover, security transparency provided by the framework promotes a trustworthy usage of mobile devices in business sector.

Significant advancement in mobile devices coupled with high speed networks have shifted personal computing towards pervasive environments. Mobile devices currently offer many value-added applications and services such as emailing, messaging, navigation, social networking, finance, and entertainment. Typically, such value-added applications have access to users’ personal information and are capable of gathering and transmitting trust sensitive information, hence posing security risks and/or privacy concerns. In this paper, we propose a context-based analytic hierarchy process (AHP) framework for eliciting context information and adapting this information with network access control measures for mobile devices. The framework enforces the execution of mobile applications inside security incubators to control the communication between mobile applications and mobile device resources. Mobile applications’ access requests are analyzed based on user's context information collected from the mobile device sensors and the application network access control configuration. We use the Facebook mobile application, as a test case, to evaluate our proposed framework. Evaluation results have demonstrated the efficacy of the framework in providing network access control measures based on real-time assessment of user's context