Performance Optimization - Evalyze Model and Generic Dashboards
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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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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 |
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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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1799138136645697536 |