Abstract

Abstract
Big data is a term that has risen to prominence describing data that exceeds the processing capacity of conventional database systems. Big data is a disruptive force that will affect organizations across industries, sectors, and economies. Hidden in the immense volume, variety, and velocity of data that is produced today is new information, facts, relationships, indicators, and pointers that either could not be practically discovered in the past, or simply did not exist before. This new information, effectively captured, managed, and analyzed, has the power to enhance profoundly the effectiveness of government. This chapter looks to the main challenges and issues that will have to be addressed to capture the full potential of big data. Additionally, the authors present a conceptual framework for big data analysis structured in there layers: (a) data capture and preprocessing, (b) data processing and interaction, and (c) auxiliary tools. Each has a different role to play in capturing, processing, accessing, and analyzing big data.

Abstract
The convergence of the voice and data worlds is introducing exciting opportunities to companies. As a consequence, Voice over IP (VoIP) technology is attracting increasing attention and interest in the industry. Flexibility and cost efficiency are the key factors luring enterprises to transition to VoIP. However, voice services also introduce a new level of vulnerability to the network. This chapter categorizes and analyzes the most common security threats of a VoIP solution in a corporate environment. Besides that, the authors discuss the most relevant security policies that could have been adopted to mitigate the security vulnerabilities introduced by VoIP. These new policies and practices can have a positive impact on the security of the whole network, not just voice communications.

Abstract

Abstract
The systematic review of the literature is a fundamental methodology for analyzing critically the existing literature on a given research theme. They are designed to be methodical, replicable and guide the author in identifying the main lines of investigation and conclusions in each scientific domain and, in addition, help them in the identification of new directions of research. However, the systematic review process is typically viewed as too heterogeneous, complex and time-consuming. In this sense, it is pertinent to propose a new approach for conducting systematic reviews that may be more agile, not only in terms of development, but also in the analysis of the results of a systematic review process. This article presents a canvas framework for conducting a systematic review composed of nine blocks and based on a set of identified good practices found in the literature, in which it is possible to easily identify all the steps of the process, options taken, and main results.

Abstract