Self-service business intelligence data analytics

Information systems bring competitive advantages to companies when they know how to use them to their full potential. Business intelligence systems can garner large volumes of data and convert it into information but have the disadvantage of having associated high implementation costs both structurally and qualified people. Then comes Self Service Business Intelligence which provides companies with much lower costs of extracting information from their systems. This work arises from Tecmic’s need to extract information in the form of reports and dashboards from the incident system it has currently implemented. This system has limited information extraction and handling capabilities to help company managers make informed decisions about customer reported incidents. In order to address this problem, it was proposed to implement the Self-Service Business Intelligence software from Microsoft, Power BI. This work details all the preparatory steps to import the data into Power BI as well as an analysis of the results obtained. Additionally, through reports created in Power BI, it is explored what inefficiencies can be tackled in order to improve company performance and drive down the number of services created.Os sistemas de informação trazem vantagens competitivas para as empresas que retiram máximo proveito deles. Os sistemas de business intelligence podem reunir grandes volumes de dados e convertê-los em informação, mas têm a desvantagem de ter elevados custos associados, estruturalmente e de trabalhadores qualificados. Surge então o Self Service Business Intelligence, que possibilita às empresas custos muito mais baixos de extrair informação de seus sistemas de informação. Este trabalho surge da necessidade da Tecmic de extrair informação sob forma de relatórios e dashboards do sistema de incidentes que tem atualmente implementado. Este sistema tem capacidades limitadas no que diz respeito à extração e tratamento de informação o que dificulta os gestores da empresa de tomar decisões informadas sobre incidentes relatados pelos clientes. Para resolver esse problema, foi proposto implementar o software de Self-Service Business Intelligence da Microsoft, o Power BI. Este trabalho detalha todas as etapas preparatórias para importar os dados para o Power BI, bem como uma análise sobre os resultados obtidos. Adicionalmente, por meio de relatórios criados no Power BI, são exploradas as ineficiências que podem ser enfrentadas para melhorar o desempenho da empresa e diminuir o número de serviços criados

Self-Service Business Intelligence

Os sistemas de gestão da produção nas empresas industriais produzem grandes quantidades de dados, mas de onde nem sempre é fácil retirar os indicadores necessários à tomada de decisão. A resolução deste problema é o objetivo das ferramentas de processamento analítico (Business Intelligence), que extraem a informação relevante dos sistemas operacionais e produzem os relatórios pedidos pelos gestores, mas, muitas vezes, recorrendo ao auxílio de especialistas.A necessidade de ter um departamento de TI como intermediário gera atrasos, reduzindo a capacidade de decisão da empresa, pelo que houve a necessidade de criar ferramentas de Self-Service Business Intelligence (SSBI). Estas permitem que colaboradores sem conhecimentos de TI consigam interrogar a base de dados, obtendo a informação que desejam de imediato, para além de poderem explorar mais e melhor a informação armazenada.A Critical Manufacturing (CMF), empresa onde esta dissertação foi realizada, é uma empresa de desenvolvimento de software com soluções gerais de BI e SSBI para o seu sistema de gestão de linhas de produção (MES) cmNavigo. No entanto, há muitas empresas sem disponibilidade financeira para adquirir estas soluções, pelos custos consideráveis no licenciamento e infraestrutura, mas que, mesmo assim, pretendem obter alguns dos seus benefícios.O objetivo desta dissertação é integrar no cmNavigo uma ferramenta protótipo de SSBI, que permita a não especialistas interrogar os dados e produzir dashboards através de uma interface gráfica. Para isso, selecionam-se algumas ferramentas de SSBI e de construção e visualização de dashboards e avaliam-se as suas abordagens, funcionalidades, vantagens e desvantagens, determinando-se qual o melhor caminho a tomar para o projeto. Escolhida a ferramenta, são estudadas abordagens diferentes à implementação de um modelo de dados simplificado, que permitem ao utilizador final a interação com os dados que considere mais relevantes.The production management systems in industrial companies produce large amounts of data, but it is not always easy to take the necessary indicators for decision making. Solving this issue is the purpose of analytical processing tools (Business Intelligence), that extract relevant information from the operating systems and produce the reports requested by the managers, but frequently using the help of experts.The need to have an IT department as an intermediary generates delays, reducing the company's decision-making capacity, so there was a need to create tools of Self-Service Business Intelligence (SSBI). These allow employees without IT knowledge to interrogate the database, obtaining the information they desire immediately, in addition to being able to better explore the information stored.Critical Manufacturing (CMF), the company where this dissertation was made, is a software development company with general BI and SSBI solutions for its own production management system (MES) cmNAVIGO. However, there are many companies without the funds to purchase these solutions, due to the considerable costs in licensing and infrastructure, but nevertheless wish to obtain some of their benefits.The aim of this work is to integrate one SSBI prototype tool into cmNAVIGO, allowing non-experts to interrogate the data and produce dashboards through a graphical interface. To do this, some tools SSBI and dashboard builders were selected and evaluated on their approaches, features, advantages and disadvantages, to determine the best path for the project. With the tool chosen, different approaches to the implementation of a simplified data model were studied, allowing the end user to interact with the data he considers most relevant

Self-Service Business Intelligence

Os sistemas de gestão da produção nas empresas industriais produzem grandes quantidades de dados, mas de onde nem sempre é fácil retirar os indicadores necessários à tomada de decisão. A resolução deste problema é o objetivo das ferramentas de processamento analítico (Business Intelligence), que extraem a informação relevante dos sistemas operacionais e produzem os relatórios pedidos pelos gestores, mas, muitas vezes, recorrendo ao auxílio de especialistas.A necessidade de ter um departamento de TI como intermediário gera atrasos, reduzindo a capacidade de decisão da empresa, pelo que houve a necessidade de criar ferramentas de Self-Service Business Intelligence (SSBI). Estas permitem que colaboradores sem conhecimentos de TI consigam interrogar a base de dados, obtendo a informação que desejam de imediato, para além de poderem explorar mais e melhor a informação armazenada.A Critical Manufacturing (CMF), empresa onde esta dissertação foi realizada, é uma empresa de desenvolvimento de software com soluções gerais de BI e SSBI para o seu sistema de gestão de linhas de produção (MES) cmNavigo. No entanto, há muitas empresas sem disponibilidade financeira para adquirir estas soluções, pelos custos consideráveis no licenciamento e infraestrutura, mas que, mesmo assim, pretendem obter alguns dos seus benefícios.O objetivo desta dissertação é integrar no cmNavigo uma ferramenta protótipo de SSBI, que permita a não especialistas interrogar os dados e produzir dashboards através de uma interface gráfica. Para isso, selecionam-se algumas ferramentas de SSBI e de construção e visualização de dashboards e avaliam-se as suas abordagens, funcionalidades, vantagens e desvantagens, determinando-se qual o melhor caminho a tomar para o projeto. Escolhida a ferramenta, são estudadas abordagens diferentes à implementação de um modelo de dados simplificado, que permitem ao utilizador final a interação com os dados que considere mais relevantes.The production management systems in industrial companies produce large amounts of data, but it is not always easy to take the necessary indicators for decision making. Solving this issue is the purpose of analytical processing tools (Business Intelligence), that extract relevant information from the operating systems and produce the reports requested by the managers, but frequently using the help of experts.The need to have an IT department as an intermediary generates delays, reducing the company's decision-making capacity, so there was a need to create tools of Self-Service Business Intelligence (SSBI). These allow employees without IT knowledge to interrogate the database, obtaining the information they desire immediately, in addition to being able to better explore the information stored.Critical Manufacturing (CMF), the company where this dissertation was made, is a software development company with general BI and SSBI solutions for its own production management system (MES) cmNAVIGO. However, there are many companies without the funds to purchase these solutions, due to the considerable costs in licensing and infrastructure, but nevertheless wish to obtain some of their benefits.The aim of this work is to integrate one SSBI prototype tool into cmNAVIGO, allowing non-experts to interrogate the data and produce dashboards through a graphical interface. To do this, some tools SSBI and dashboard builders were selected and evaluated on their approaches, features, advantages and disadvantages, to determine the best path for the project. With the tool chosen, different approaches to the implementation of a simplified data model were studied, allowing the end user to interact with the data he considers most relevant

User Related Challenges of Self-Service Business Intelligence

Self-service Business Intelligence (SSBI) is an upcoming trend that allows non-technical casual users to use Business Intelligence (BI) in a self-reliant manner without the support of technical power users. Many organizations struggle to utilize the potential of SSBI and experience data-related and user-related SSBI implementations challenges. This study aimed at exploring user-related SSBI challenges by conducting and analyzing a total of 30 qualitative interviews with 5 BI consultants and 10 customer representatives involved in 2 SSBI implementation project teams. Analysis of the interviews revealed ten challenges related to “Self-reliant users”, seven challenges related to “creating SSBI reports” and five challenges related to “SSBI education” that differ considerably from SSBI challenges commonly discussed in literature. Awareness of these 22 challenges can help practitioners to avoid unnecessary obstacles when implementing and using SSBI, and guide SSBI researchers in simplifying the implementation process of SSBI

DATA ACCESS AND DATA QUALITY CHALLENGES OF SELF-SERVICE BUSINESS INTELLIGENCE

Self-service Business Intelligence (SSBI) is an upcoming trend that allows non-technical casual users to use BI in a self-reliant manner without the support of technical power users. Many organisations struggle to utilize the potential of SSBI and experience data-related and user-related SSBI implemen- tations challenges. This study aimed at exploring data-related SSBI challenges by conducting and analysing a total of 30 qualitative interviews with 5 BI consultants and 10 customer representatives involved in 2 SSBI implementation project teams. Analysis of the interviews revealed five challenges related to “Access and use of data” and four challenges related to “Data quality” that differ consid- erably from SSBI challenges commonly discussed in literature. Awareness of these challenges can help practitioners to avoid unnecessary obstacles when implementing and using SSBI. They can also guide SSBI researchers to simplify the implementation process of SSBI

Self-Service Business Intelligence: Konsekvenserna av flexibilitet

Dagens föränderliga och dynamiska marknad har lett till att organisationer tvingas vara flexibla för att snabbare kunna fatta beslut och anpassa sig. Vidare har detta lett till en förändring inom Business Intelligence (BI), där en nyare lösning kallad Self-Service Business Intelligence (SSBI) har vuxit fram. SSBI syftar huvudsakligen till att förbättra beslutsfattande i organisationer genom att göra processen för beslutsfattande snabbare och ge användare mer flexibilitet. Flexibiliteten ger användare möjlighet att betjäna sig själva i arbetet för att ta fram beslutsunderlag. Uppsatsen argumenterar för att den flexibilitet som SSBI är tänkt att medföra inte kommer utan oproblematiska konsekvenser. Uppsatsen presenterar teoretiska förhållningssätt till SSBI som beskriver möjligheter och utmaningar med SSBI. Teorin jämförs därefter med empiri som utvunnits från sex intervjuer med olika leverantörer av BI-lösningar. Studien har identifierat att för att uppnå ändamålsenlig flexibilitet krävs det att datakvaliteten och tillförlitligheten säkerställs och att adekvat utbildning ges. Uppsatsen ifrågasätter därför begreppet “self-service” eftersom den eftersträvade effekten att låta användare betjäna sig själva inte sker utan att konsekvenserna av flexibilitet beaktas

Self Service Business Intelligence: An Analysis of Tourists Preferences in Kosovo

The purpose of this paper is to analyze the preferences of tourists in Kosovo through the data from TripAdvisor.com. Top things to do in Kosovo, will be analyzed through the comments of tourists in TripAdvisor.com. By analyzing the data with PowerBI, will be analyzed what are the most preferred things to do and what the tourists like the most in Kosovo. This paper will contribute on defining the preferences of tourists in Kosovo, it also can help tourism to invest and attract more tourists in specific areas or improve and invest in places less preferred by tourists

A Maturity Model of Data Modeling in Self-Service Business Intelligence Software

Although Self-Service Business Intelligence (SSBI) is continually being adopted in various industries, there is a lack of research focused on data modeling in SSBI. This research aims to fill that research gap and propose a maturity model for SSBI data modeling which is generalizeable between different software and applicable for users of all technical backgrounds. Through extensive literature review, a five-tier maturity model was proposed, explained, and instantiated in PowerBI and Tableau. The testing of the model was found to be simple and intuitive, and the research concludes that the model is applicable to enterprise SSBI environments. This research is limited to SSBI software and does not consider architecture specifications such as data warehouse or hardware limitations, and could be expanded in future research to include those considerations