Performance Optimization - Evalyze Model and Generic Dashboards

Detalhes bibliográficos
Autor(a) principal: Gomes, Virgínia Teodoro
Data de Publicação: 2023
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/152310
Resumo: Internship Report presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization in Information Analysis and Management
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spelling Performance Optimization - Evalyze Model and Generic DashboardsPower BIData ModelsPerformance OptimizationEfficiencyData WarehouseDashboardsKPIAIInternship Report presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization in Information Analysis and ManagementCloser is a Data Science company specialized in Business Intelligence, Advanced Analytics and Artificial Intelligence. Their purpose is to be at the forefront of innovation, and my intention in this internship was to contribute with my knowledge, work, and dedication to improve the data models that already exist and to create new ones that fills the needs of the company. Closer received feedback from several users that some of the dashboard visual elements present in Evalyze took too long to load and my goal was to achieve the highest performance by reducing errors, non-conformities and provide standardized responses to ensure a superior level of service, thus, controlling the efficiency more precisely. Throughout the internship I used SQL and Power BI on a daily basis to improve models and create new ones. I also created several dashboards in Power BI in accordance with the team's needs. In this essay, it will be explained the several techniques that were used to improve the existent models in Closer, more specifically one that lacked the most in efficiency, taking too much time to execute basic tasks, therefore required improvement as well as innovative upgrades. Also, I have built new models that Closer required and wished to have, allowing to create new dashboards to have clear visualizations of its business. As for the data sources used for the dashboards, it was stored on Data Warehouse, particularly in tables where data regarding Evalyze operations and Azure SQL on prem database. Azure SQL Database is an always-up-to-date, fully managed relational database service built for the cloud. Regarding the modeling of data, Power BI is utilized and make use of a star model. Finally, at the visualization level, reports were developed based on the model previously developed in Power BI (figures 27 and 28 in annexes). The data I worked with was about what was done in Evalyze, Closer's software. The data refer to the number of open activities, activities handled, activity resolution times and average productive times. This data is registered in the database and in turn goes to the data warehouse. Evalyze software is a tool that focuses on real-time operations management, improvement, assessment, and analysis. One of the features present in this software is the availability of generic dashboards that allow the customer to follow the evolution of the main business KPI's. To put it briefly, Evalyze is a web tool that automatically and intelligently distributes activities, increasing operations productivity. The process is done through Artificial Intelligence algorithms based on SLA’s, AHT, customers’ score, skills and operator’s availability, ensuring that the distribution is made activity-to-activity and in real time, according to what is the highest priority for the company, without the possibility of choice by operators. Built-in Artificial Intelligence (Machine Learning) enables the use of analytical/mathematical methods to automate end-to-end processes, incorporate business rules, and learn and evolve over time.Damásio, Bruno Miguel PintoRUNGomes, Virgínia Teodoro2023-05-02T13:40:35Z2023-04-132023-04-13T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/152310TID:203277414enginfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T05:34:37Zoai:run.unl.pt:10362/152310Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:54:51.451633Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Performance Optimization - Evalyze Model and Generic Dashboards
title Performance Optimization - Evalyze Model and Generic Dashboards
spellingShingle Performance Optimization - Evalyze Model and Generic Dashboards
Gomes, Virgínia Teodoro
Power BI
Data Models
Performance Optimization
Efficiency
Data Warehouse
Dashboards
KPI
AI
title_short Performance Optimization - Evalyze Model and Generic Dashboards
title_full Performance Optimization - Evalyze Model and Generic Dashboards
title_fullStr Performance Optimization - Evalyze Model and Generic Dashboards
title_full_unstemmed Performance Optimization - Evalyze Model and Generic Dashboards
title_sort Performance Optimization - Evalyze Model and Generic Dashboards
author Gomes, Virgínia Teodoro
author_facet Gomes, Virgínia Teodoro
author_role author
dc.contributor.none.fl_str_mv Damásio, Bruno Miguel Pinto
RUN
dc.contributor.author.fl_str_mv Gomes, Virgínia Teodoro
dc.subject.por.fl_str_mv Power BI
Data Models
Performance Optimization
Efficiency
Data Warehouse
Dashboards
KPI
AI
topic Power BI
Data Models
Performance Optimization
Efficiency
Data Warehouse
Dashboards
KPI
AI
description Internship Report presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization in Information Analysis and Management
publishDate 2023
dc.date.none.fl_str_mv 2023-05-02T13:40:35Z
2023-04-13
2023-04-13T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/152310
TID:203277414
url http://hdl.handle.net/10362/152310
identifier_str_mv TID:203277414
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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