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p>Data visualization is an effort which aims to communicate data effectively and clearly to the audience through graphical
representation. Data visualization efforts must be coordinated with an understanding into the Cognitive Learning Theory (CLT). In the sales domain, sales data visualization are made possible with the available Business Intellig...
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... In graylevel images, compression algorithms are simple to visualize as preference can be the 2D spatial domain plus one dimension for illumination then they can be represented by a 3D visualization. In RGB, color spectrum visualization is complex as there are further dimensions that human eyes can perceive [8]. We can consider color variables to identify image intensity; however it eventually brings us back to a graylevel image instead. ...
A fundamental factor of digital image compression is the conversion processes. The intention of this process is to understand the shape of an image and to modify the digital image to a grayscale configuration where the encoding of the compression technique is operational. This article focuses on an investigation of compression algorithms for images with artistic effects. A key component in image compression is how to effectively preserve the original quality of images. Image compression is to condense by lessening the redundant data of images in order that they are transformed cost-effectively. The common techniques include discrete cosine transform (DCT), fast Fourier transform (FFT), and shifted FFT (SFFT). Experimental results point out compression ratio between original RGB images and grayscale images, as well as comparison. The superior algorithm improving a shape comprehension for images with grahic effect is SFFT technique.
... As next steps, we plan to conduct interviews with BIA experts and users to validate and extend our SLR outcomes and supplement the results with contemporary issues from practitioners. Although some authors rely on theories and concepts (e.g., Jie et al., 2018;Saeed and Abdinnour, 2011) or illustrate the SSBIA business value, the domain lacks a solid foundation with regard to systematic methods and an established theory still needs to materialize to date. We hope that our SLR can serve as a reference for scholars in the broader field of SSBIA and the aspects that should be considered when investigating related concepts and solutions. ...
Self-Service Business Intelligence and Analytics (SSBIA) is an upcoming approach and trend that enables casual business users to prepare and analyze data with easy-to-use Business Intelligence and Analytics (BIA) systems without being reliant on expert support or power users to perform their (complex) analytical tasks easier and faster than before. Despite a strong interest of scholars and practitioners in SSBIA, the understanding about its underlying characteristics is limited. Furthermore, there is a lack of a structured and systematic form in which SSBIA research can be classified. Against this backdrop, this article showcases the current state-of-the-art of SSBIA research along four key areas in the field: (1) perspectives on SSBIA, (2) user roles involved, (3) required expertise, and (4) supported levels of self-service. Analyzing 60 articles, our main contribution resides in the synopsis of SSBIA literature in these four areas. For instance, we illustrate that there exist three perspectives of SSBIA: artefact-centric (45% of analyzed studies), user-centric (82%), and governance-centric (25%). On the basis of our analysis, we suggest promising avenues, which will support scholars in their endeavors on how to pursue with future avenues in the field of SSBIA (for e.g., understanding the trade-off between top-down and bottom-up capabilities).
... The ability of Business Intelligence (BI) system to analyze considerable volume of data into useful information has made it a valuable technological tool for organizations [1]. The role of BI that turned the data into knowledge to facilitate users and aid the decision making process has made the system well recognized by organizations, including the manufacturing. ...
span>Business Intelligence (BI) offered many advantages to organizations adopting the system such as improved decision making and boost organization’s performance. The lack of research on the continuous usage of BI in manufacturing motivates the initiative in this study to have an understanding of the determinants that influenced it. The study proposed a model of individual-related determinants that lead to the continuous usage of BI in manufacturing. A model integrating Unified Theory of Acceptance and Use of Technology (UTAUT) and Information System Continuance Model (ISCM) will be developed. The model will portray 20 hypotheses and 11 determinants leading continuance usage of BI. Data will be collected through survey questionnaires instrument and validated using Structural Equation Modelling (SEM). The result is hoping to show significant relationships between the determinants towards the continuous usage of BI in manufacturing. The study can potentially be used to guide manufacturers and practitioners for considerations in implementing BI in the manufacturing industry. </span
