Business Intelligence -järjestelmä päätöksentekijöiden tukena asiantuntijayrityksessä

Työn tarkoituksena oli kartoittaa ja tehdä esiselvitys Business Intelligencen(BI) mahdollisuuksista tiedon hallinnassa. Tavoitteena oli selvittää, kuinka yritys voi tietotekniikan avulla paremmin hyödyntää operatiivisten järjestelmien tuottamia tietoja päätöksenteon tukena. Työssä sovellettiin konstruktiivista tutkimusotetta. Business Intelligence -teknologiaan tutustuttiin aluksi kirjallisuuden avulla. Ongelmaa lähestyttiin selvittämällä kohdeyrityksen tiedonhallinnan nykytila ja siihen liittyvät ongelmat. Käyttäjävaatimukset selvitettiin strukturoidulla kyselytutkimuksella. Lisäksi työn empiriaosuudessa tutustuttiin kahteen Business Intelligence -toteutukseen ja arvioitiin teknologian kypsyyttä suhteessa asiakasvaatimuksiin. Tiedonhallinnalta toivottiin joustavuutta ja helppokäyttöisyyttä.Erityisesti tutkimuksessa esiin nousi se, että tiedon jakeluun tarvitaan monipuolisempia vaihtoehtoja. Käyttäjät olivat valmiita hyödyntämään uusia BI-ominaisuuksia varsin laajalti. Haastavinta tutkimuksessa oli liiketoiminnan ymmärtäminen. Suurimmat BI-teknologian puutteet havaittiin loppukäyttäjän sovelluksissa. Tietovarastointiprosessiin liittyvä teknologia todettiin toimivaksi.

Análisis de datos de accidentes de tráfico mediante soluciones big data y business intelligence

Este proyecto de final de carrera corresponde al área de inteligencia artificial y representa un caso de uso que pretende utilizar datos reales referentes a accidentes de tráfico (datos de accidentes, muertos, heridos, etc.) y analizarlas conjuntamente con datos que puedan tener una posible relación con los accidentes como el parque de vehículos, las temperaturas de la zona de los accidentes, etc. con la finalidad de poder obtener las posibles relaciones causa-efecto.

Business intelligence –järjestelmä integraation tukena kansainvälisessä yrityksessä

Business intelligencellä tarkoitetaan liiketoimintatiedon hallintaan liittyviä prosesseja ja tekniikoita. Se pitää sisällään tiedon keräämiseen, tallentamiseen, analysointiin ja jakamiseen käytettyt tuotteet, tekniikat ja prosessit, joiden tavoitteena on auttaa yrityksen työntekijöitä liiketoimintaan liittyvässä päätöksenteossa. Tutkimuksen tavoitteena on tutkia uuden yritysryhmän laajuisen BI-tietojärjestelmän suunnitteluun ja käyttöönotoon liittyviä seikkoja ja luoda valmiudet BI-tietojärjestelmän kehitys- ja käyttöönottoprojektin kohdeyrityksessä, jonka toimiala on kansainvälinen terveydenhoitoalan tukkuliiketoiminta. Uuden BI-järjestelmän halutaan tukeva yritysryhmän yritysten välistä integraatiota ja tehostavan tiedonhakuun ja analysointiin liittyviä prosesseja. Tutkimus toteutettiin konstruktiivisena tutkimuksena, joka kattaa kohdeyrityksen IT-arkkitehtuurin, tietosisällön, prosessit ja organisaation raportoinnin kannalta. Lisäksi työssä suoritettiin ohjelmistovertailu kahden markkinoilla toimivan merkittävän ohjelmistotalon BI-tuotteiden välillä. Työssä havaittiin, että BI-projekti on laaja-alainen ja suuri hanke, joka ulottuu läpi koko organisaation. BI-ohjelmiston tehokas hyödyntäminen asettaa vaatimuksia erityisesti taustajärjestelmien tiedon huolelliseen mallintamiseen liittyen. Työssä saatiin pilotoinnin kautta käytännön kokemuksia uudesta järjestelmästä ja sen tarjoamista mahdollisuuksista kohdeyrityksessä.

Tietovaraston latausprosessin kehittämisen osittainen automatisointi Microsoft SQL Server 2008 -ympäristössä

Tässä työssä tutkitaan tietovaraston latausprosessin kehittämisen nopeuttamista Mic-rosoft SQL Server 2008 -ympäristössä. Työn teoriaosuudet on tarkoitettu tukemaan sekä työn tutkimus- että käytännönosia. Aiheeseen liittyviä tutkimuksia käytiin läpi parhaiden latausprosessin kehittämiseen kuluvaa aikaa vähentävien tapojen selvittä-miseksi. Nykytutkimus keskittyy valmistajasta riippumattomien mallien kehittämiseen ja valmistajakohtaisen latausprosessin luomiseen näiden mallien pohjalta. Yleinen konsensus parhaan mallin suhteen kuitenkin puuttuu. Aiheeseen liittyvien tutkimusten pohjalta esitetään arkkitehtuuri, joka saattaisi tule-vaisuudessa vähentää latausprosessin kehittämiseen kuluvaa aikaa huomattavasti. Tästä arkkitehtuurista luotiin yksinkertaistettu versio sekä siihen pohjautuva sovellus nopeuttamaan latausprosessin kehittämistä Microsoftin ETL-työkalulla.

Ensuring the efficient utilization of Business Intelligence

In recent years, chief information officers (CIOs) around the world have identified Business Intelligence (BI) as their top priority and as the best way to enhance their enterprises competitiveness. Yet, many enterprises are struggling to realize the business value that BI promises. This discrepancy causes important questions, for example: what are the critical success factors of Business Intelligence and, more importantly, how it can be ensured that a Business Intelligence program enhances enterprises competitiveness. The main objective of the study is to find out how it can be ensured that a BI program meets its goals in providing competitive advantage to an enterprise. The objective is approached with a literature review and a qualitative case study. For the literature review the main objective populates three research questions (RQs); RQ1: What is Business Intelligence and why is it important for modern enterprises? RQ2: What are the critical success factors of Business Intelligence programs? RQ3: How it can be ensured that CSFs are met? The qualitative case study covers the BI program of a Finnish global manufacturer company. The research questions for the case study are as follows; RQ4: What is the current state of the case company’s BI program and what are the key areas for improvement? RQ5: In what ways the case company’s Business Intelligence program could be improved? The case company’s BI program is researched using the following methods; action research, semi-structured interviews, maturity assessment and benchmarking. The literature review shows that Business Intelligence is a technology-based information process that contains a series of systematic activities, which are driven by the specific information needs of decision-makers. The objective of BI is to provide accurate, timely, fact-based information, which enables taking actions that lead to achieving competitive advantage. There are many reasons for the importance of Business Intelligence, two of the most important being; 1) It helps to bridge the gap between an enterprise’s current and its desired performance, and 2) It helps enterprises to be in alignment with key performance indicators meaning it helps an enterprise to align towards its key objectives. The literature review also shows that there are known critical success factors (CSFs) for Business Intelligence programs which have to be met if the above mentioned value is wanted to be achieved, for example; committed management support and sponsorship, business-driven development approach and sustainable data quality. The literature review shows that the most common challenges are related to these CSFs and, more importantly, that overcoming these challenges requires a more comprehensive form of BI, called Enterprise Performance Management (EPM). EPM links measurement to strategy by focusing on what is measured and why. The case study shows that many of the challenges faced in the case company’s BI program are related to the above-mentioned CSFs. The main challenges are; lack of support and sponsorship from business, lack of visibility to overall business performance, lack of rigid BI development process, lack of clear purpose for the BI program and poor data quality. To overcome these challenges the case company should define and design an enterprise metrics framework, make sure that BI development requirements are gathered and prioritized by business, focus on data quality and ownership, and finally define clear goals for the BI program and then support and sponsor these goals.

Heat Demand Forecasting Models’ Development: Use of Data Mining Tools in SQL Server Analysis Services

This thesis introduces heat demand forecasting models which are generated by using data mining algorithms. The forecast spans one full day and this forecast can be used in regulating heat consumption of buildings. For training the data mining models, two years of heat consumption data from a case building and weather measurement data from Finnish Meteorological Institute are used. The thesis utilizes Microsoft SQL Server Analysis Services data mining tools in generating the data mining models and CRISP-DM process framework to implement the research. Results show that the built models can predict heat demand at best with mean average percentage errors of 3.8% for 24-h profile and 5.9% for full day. A deployment model for integrating the generated data mining models into an existing building energy management system is also discussed.

Business Intelligence: comparação de ferramentas

Cada vez mais o tempo acaba sendo o diferencial de uma empresa para outra. As empresas, para serem bem sucedidas, precisam da informação certa, no momento certo e para as pessoas certas. Os dados outrora considerados importantes para a sobrevivência das empresas hoje precisam estar em formato de informações para serem utilizados. Essa é a função das ferramentas de “Business Intelligence”, cuja finalidade é modelar os dados para obter informações, de forma que diferencie as ações das empresas e essas consigam ser mais promissoras que as demais. “Business Intelligence” é um processo de coleta, análise e distribuição de dados para melhorar a decisão de negócios, que leva a informação a um número bem maior de usuários dentro da corporação. Existem vários tipos de ferramentas que se propõe a essa finalidade. Esse trabalho tem como objetivo comparar ferramentas através do estudo das técnicas de modelagem dimensional, fundamentais nos projetos de estruturas informacionais, suporte a “Data Warehouses”, “Data Marts”, “Data Mining” e outros, bem como o mercado, suas vantagens e desvantagens e a arquitetura tecnológica utilizada por estes produtos. Assim sendo, foram selecionados os conjuntos de ferramentas de “Business Intelligence” das empresas Microsoft Corporation e Oracle Corporation, visto as suas magnitudes no mundo da informática.

Open business intelligence: on the importance of data quality awareness in user-friendly data mining

Citizens demand more and more data for making decisions in their daily life. Therefore, mechanisms that allow citizens to understand and analyze linked open data (LOD) in a user-friendly manner are highly required. To this aim, the concept of Open Business Intelligence (OpenBI) is introduced in this position paper. OpenBI facilitates non-expert users to (i) analyze and visualize LOD, thus generating actionable information by means of reporting, OLAP analysis, dashboards or data mining; and to (ii) share the new acquired information as LOD to be reused by anyone. One of the most challenging issues of OpenBI is related to data mining, since non-experts (as citizens) need guidance during preprocessing and application of mining algorithms due to the complexity of the mining process and the low quality of the data sources. This is even worst when dealing with LOD, not only because of the different kind of links among data, but also because of its high dimensionality. As a consequence, in this position paper we advocate that data mining for OpenBI requires data quality-aware mechanisms for guiding non-expert users in obtaining and sharing the most reliable knowledge from the available LOD.

La Business Intelligence per il monitoraggio delle vendite: il caso Ducati Motor Holding

“La Business Intelligence per il monitoraggio delle vendite: il caso Ducati Motor Holding”. L’obiettivo di questa tesi è quello di illustrare cos’è la Business Intelligence e di mostrare i cambiamenti verificatisi in Ducati Motor Holding, in seguito alla sua adozione, in termini di realizzazione di report e dashboard per il monitoraggio delle vendite. L’elaborato inizia con una panoramica generale sulla storia e gli utilizzi della Business Intelligence nella quale vengono toccati i principali fondamenti teorici: Data Warehouse, data mining, analisi what-if, rappresentazione multidimensionale dei dati, costruzione del team di BI eccetera. Si proseguirà mediante un focus sui Big Data convogliando l’attenzione sul loro utilizzo e utilità nel settore dell’automotive (inteso nella sua accezione più generica e cioè non solo come mercato delle auto, ma anche delle moto), portando in questo modo ad un naturale collegamento con la realtà Ducati. Si apre così una breve overview sull’azienda descrivendone la storia, la struttura commerciale attraverso la quale vengono gestite le vendite e la gamma dei prodotti. Dal quarto capitolo si entra nel vivo dell’argomento: la Business Intelligence in Ducati. Si inizia descrivendo le fasi che hanno fino ad ora caratterizzato il progetto di Business Analytics (il cui obiettivo è per l'appunto introdurre la BI i azienda) per poi concentrarsi, a livello prima teorico e poi pratico, sul reporting sales e cioè sulla reportistica basata sul monitoraggio delle vendite.

Estágio TAP/Megasys - Data Warehouse & Reporting

Mestrado em Gestão de Sistemas de Informação

Framework genérica de business intelligence para suporte financeiro

Actualmente, não existem ferramentas open source de Business Intelligence (BI) para suporte à gestão e análise financeira nas empresas, de acordo com o sistema de normalização contabilística (SNC). As diferentes características de cada negócio, juntamente com os requisitos impostos pelo SNC, tornam complexa a criação de uma Framework financeira genérica, que satisfaça, de forma eficiente, as análises financeiras necessárias à gestão das empresas. O objectivo deste projecto é propor uma framework baseada em OLAP, capaz de dar suporte à gestão contabilística e análise financeira, recorrendo exclusivamente a software open source na sua implementação, especificamente, a plataforma Pentaho. Toda a informação contabilística, obtida através da contabilidade geral, da contabilidade analítica, da gestão orçamental e da análise financeira é armazenada num Data mart. Este Data mart suportará toda a análise financeira, incluindo a análise de desvios orçamentais e de fluxo de capitais, permitindo às empresas ter uma ferramenta de BI, compatível com o SNC, que as ajude na tomada de decisões.

Business Intelligence para PME: a informação contabilística no suporte à decisão.

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação.