Rapporten inleds med en beskrivning av WM-datas Network Management struktur och Reporting Management behov. Därefter följer en beskrivning av de två analys tekniker Datamining och On Line Analytical Processing (OLAP) vilka är de mest använda databasbaserade tekniker. Verktyget Tivoli Decision Support (TDS) är ett stödssystem som ska underlätta för beslutsfattare inom organisationen. TDS baseras på OLAP ? tekniken och rapporten visar avslutningsvis de möjligheter som verktyget ger avseende WM-datas Reporting Management. / Christine Svensson 0454-14926 Susanne Strandberg 0456-22824

El presente proyecto se realizó para la Empresa GyM S.A., esta organización se dedica a la construcción de obras civiles, obras electromecánicas y edificaciones, además brinda servicios a las principales Empresas del Perú y también cuenta con proyectos fuera del país. El propósito de nuestra investigación es demostrar cómo la Inteligencia de Negocios puede dar solución a la problemática actual de la corporación que, debido a la enorme cantidad de datos que procesan los sistemas con que trabajan, actualmente no cuentan con un control ni con una manera automatizada de consolidar toda esa información. Nuestra propuesta consta de integrar los sistemas de la empresa mediante técnicas presentadas por la Inteligencia de Negocios, con el fin, de que en base a la construcción de indicadores, reportes de análisis de la información, entre otras herramientas, podamos brindar una solución que sea de apoyo para la toma de decisiones en la empresa y así la alta gerencia pueda ejecutar las medidas correctivas en caso se amerite. Nuestro análisis demostrará que la solución es sumamente rentable, con respecto al costo que implica el proceso de realizar una consolidación manual de la información mensualmente, como es requerido. Así mismo, muestra efectos positivos en la utilización de Inteligencia de Negocios para la organización, debido a la calidad y mejor control de la información.

This thesis is focused on using data mining in Business Intelligence solution. The goal of this thesis is implementation of data mining in Business Intelligence solution. Integration of these technologies is posible to obtain synergic effect. The thesis is made in context of academic project Farfalia and results are used in the project. The goal of project is to create component for a new form of reporting and that is using data mining as a tool for data analysis. The benefit of the implementation is automatic browsing of multidimensional data cube / multidimensional data model to find interesting KPI trends, interesting patterns or anomalies in the data. Tasks of data mining are realized by analytic models that are created in this thesis. These models are prepared in R language. Developed scripts of models are universal and after their adjustment by constraints of specific project are useable in any BI solution.

This diploma thesis deals with building of large Data Warehouses on Microsoft SQL Server 2008 platform. First part of the thesis discuss about news in MS SQL Server 2008, which I have considered as being important for Business Intelligence area. Following chapters are focused on approach to implementation of real Data Warehouse for Customs Administration of Czech Republic on MS SQL Server 2008 basis. These parts of the thesis cover specifics of the Customs Administration of Czech Republic, current state of Data Warehouse and reasons for migrating to MS SQL Server 2008. Further the thesis describes both logical and physical architecture of proposed solution and a way of implementation Data Warehouse on MS SQL Server 2008. The main aim of the thesis is to create a list of critical success factors (CSF) of building large Data Warehouses on MS SQL Server 2008 platform. It's not only plain list CSF, but rather the best practices for MS SQL Server Data Warehouses implementation. The most significant contribution of this thesis is that it offers instruction manual for designing and implementing large Data Warehouse on MS SQL Server basis. Background for the creation of summary of CSV and recommendations were vendor's publications and especially my own experience with the product. My colleagues from company Adastra gave me an advisory opinion as well.

This dissertation titled Designing Project Business Intelligence focuses on data warehouse in a medium-sized company. The theoretical portion of the thesis describes the topic of data warehouse and dimensional modeling. In the first theoretical chapter, I compare and contrast two approaches to datawarehouse building - Bill Inmon's and Ralph Kimball's. Then, basic terminology used in the field, principles of dimensional modeling and various approaches of database use will be described. Furthermore, the thesis illustrates the role of the Mondrian system as a mediator between the relational database and the OLAP server. Possible uses of the MDX language in working with multidimensional databases are outlined. The theoretical portion of the thesis ends with a description of the applicational interface XMLA, which can be used for facilitation communication between applications and the OLAP server. The practice-oriented portion of the thesis includes a complete design of the Business Intelligence project. The project is divided into the following parts: Feasibility Study, Project Planing, Business Requirements, Design and Development, and Deployment and Maintenance. The entire project operates exclusively on Open Source Software. Consequently, the project shows that small and medium-sized companies can afford to run a fully operating Business Intelligence system.

Tor is a distributed network providing privacy and anonymity on the Internet. Information about Tor is publicly available in a form of consensus documents. Existing tools that are able to display this information do not provide both historical and detailed view of it. A tool named Consensus Parser that provides a detailed, historical view of this information and extends it with geolocation and DNS information, was created as a part of TARZAN research project at Brno University of Technology. It stores the information in regular files on disk and makes it accessible via REST API. This thesis extends Consensus Parser with MariaDB ColumnStore database with a schema designed to conform to OLAP needs. The searching capabilities of Consensus Parser were enhanced by adding 109 new endpoints to 12 existing ones and adding the ability to limit the retrieved information to certain fields only. Disk space needed for storing the information was reduced by a factor of five.

This thesis deals with the design and implementation of operational and financial reports using BI tools. Theoretical part describes basic principles of Business Intelligence, datamarts, OLAP cubes and reporting services. Several interactive reports are designed in practical part, based on users business requirements. The reports permit users to interact, drilling down from summary to detail information and jumping to related websites within intranet portal.

Thesis deals with the realization of complex Business Intelligence (BI) solution, which is an extension of current analytical layer of the company and also includes implementation of data warehouse, data cubes and report. The introductory part of the thesis describes theory of BI problematics, usage of data warehouse in Customer Realationship Management (CRM) and data-driven marketing. Later part describes specification of requirements, analysis of the current state of the company and own work. Microsoft tools and technologies were used for development of the solution.

This thesis follows up the creation of data warehouse on Microsoft SQL Server for analysis of measured railway vehicle transits, with provided weather data by Dark Sky service. Thesis represents full data warehouse design (by Kimball Group model) with ETL processes to secure data initialization and automatic updates. Thesis also shows two approaches to presentation layer on data warehouse, by Microsoft Excel (linked to multidimensional cube) and by Power BI.

I discuss in this work tools used to build dynamic web-based aplications, focusing on Ajax technology. I introduce the components of this technique, its principles, usage, advantages and disadvantages.I describe a system, which uses Ajax for helping with realization of OLAP operations through dynamic tables. There is also description of these operations included, as well as introduction to possibilities of visual representation of their results.