Browsing by Author "Huaman-Valle, Angela"

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Assessing Data Analytics Capabilities in Retail Organizations: Insights into Mining, Predictive Analytics and Machine Learning.
(World Scientific and Engineering Academy and Society., 2024-07) Pariona Luque, Rosario Blanca; Pacheco, Alex Abelardo; Vegas-Gallo, Edwin; Castanho, Rui Alexandre; Lema, Fabián; Huaman-Valle, Angela; Añaños-Bedriñana, Marco A.; Marín, Wilson; Felix-Poicon, Edwin Carlos Lenin; Loures, Ana
Nowadays, implementing data analytics is necessary to improve the collection, evaluation, analysis, and organization of data that allow the discovery of patterns, correlations, and trends that improve knowledge management, development of strategies, and decision-making in the organization. Therefore, this study aims to provide an accurate and detailed assessment of the current state of data analytics in the retail sector, identifying specific areas of improvement to strengthen knowledge management in organizations. The research is applied with a quantitative approach and non-experimental design at a descriptive and propositional level. The survey technique was used, and as a data collection instrument, a questionnaire addressed to 351 employees of companies in the retail sector concerning the variable data analysis with the dimensions of data extraction, predictive analysis, and machine learning and the variable management of the knowledge with the dimensions knowledge creation and knowledge storage. The results show that 52.99% of collaborators indicate that the level of data extraction is terrible, 57.83% indicate that the level of predictive analysis is wrong, and 54.99% express that the level of machine learning is average, which contributes to the implementation of innovative resources and solutions that promote the inclusion of a high-tech approach to address information management problems and contribution to the development of knowledge in an institution.
Tackling Noise: Technology Integration for Improved Noise Pollution Monitoring.
(SAGE Publications, 2024-02) Estrella, Ivan; Pacheco, Alex Abelardo; Marín, Wilson; Huaman-Valle, Angela; Cuba Carbajal, Nestor; Pucuhuayla-Revatta, Félix; Felix-Poicon, Edwin Carlos Lenin; Añaños-Bedriñana, Marco A.; Pacheco-Pumaleque, Liz
Noise pollution derived from motor vehicles, especially those with noisy engines, constitutes a significant challenge in urban environments, impacting quality of life and public health. In this context, the present study focuses on the implementation of an advanced technological solution: a web based system specifically designed to monitor and manage noise pollution in Tarapoto, Peru. The execution of this project was structured in 4 key phases. The first phase involved extensive data collection and definition of the project scope. In the second phase, the system architecture was established based on initial observations. The third phase focussed on evaluating and improving system functionalities, while the fourth involved rigorous testing and corrections. The successful implementation of this system led to a significant improvement in the noise pollution monitoring process, reducing reporting times and improving data-driven decision making. This project not only provides a valuable tool for authorities in the management and mitigation of noise pollution, but also encourages community awareness and active participation in the sustainable management of the urban acoustic environment.