This thesis focuses on data warehousing on technological platform TERADATA and Informatica Power Center (further only IFPC). TERADATA provides a robust database system for storage of big volume data and query processing over such data. Product Informatica Powercenter is a tool for developing of ETL processes. Both of tools belong to mature technology for large data warehouse development which stores large volumes of data over the enterprise. The thesis analyses both tools to build data warehouse and the specifics of their use in the insurance sector. The thesis is divided into two main thematic sections - theoretical and practical part. The theoretical part describes database system TERADATA and ETL tool IFPC in details, including analysis of business intelligence architecture in the insurance segment, which often uses this platform for data warehouse development. The thesis describes the architecture of database system TERADATA and the way to data storage and query processing. Then specific features, on which is necessary to focus by TERADATA data warehouse development, are characterized. Also its advantages and disadvantages are analyzed. Database system TERADATA is faced with other competing database systems. The thesis deals with general characteristics of ETL tool IFPC -- software architecture a its components. It examines the advantages and disadvantages of IFPC compared to competitors on the market. Conclusion of the theoretical part analyzes the synergies between Teradata and IFPC. The thesis explains the real benefits of combination TERADATA and IFPC. The practical part of thesis demostrates the use of tools for data warehousing development on real project Unification of client data. This project describes the entire development process in a data warehouse from business requirements through functional and technical design to implementation of ETL mapping in Informatica Power Center. It deals with bug fixing during ETL development and testing methods. The pratical part focuses on implementation of chosen mapping in IFPC which is deployed in the insurance sector. Part of this thesis is a comparison of ETL tools IFPC with SSIS ETL tool integrated in MS SQL Server 2008 R2.

This thesis deals with the application of Business Intelligence (BI) to support the corporate performance management in ISS Europe, spol. s r. o. This company provides licences and implements original software products as well as third-party software products. First, an analysis is conducted in the given company, which then serves as basis for the implementation of the BI solution that should be interconnected with the company strategies. The main goal is the implementation of a pilot BI solution to aid the monitoring and optimisation of corporate performance. Among secondary goals are the analysis of related concepts, business strategy analysis, strategic goals and systems identification and the proposition and implementation of a pilot BI solution. In its theoretical part, this thesis focuses on the analysis of concepts related to corporate performance and BI implementations and shortly describes the company together with its business strategy. The following practical part is based on the theoretical findings. An analysis of the company is carried out using the Balanced Scorecard (BSC) methodology, the result of which is depicted in a strategic map. This methodology is then supplemented by the Activity Based Costing (ABC) analytical method, which divides expenses according to assets. The results are informational data about which expenses are linked to handling individual developmental, implementational and operational demands for particular contracts. This is followed by an original proposition and the implementation of a BI solution which includes the creation of a Data Warehouse (DWH), designing Extract Transform and Load (ETL) and Online Analytical Processing (OLAP) systems and generating sample reports. The main contribution of this thesis is in providing the company management with an analysis of company data using a multidimensional perspective which can be used as basis for prompt and correct decision-making, realistic planning and performance and product optimisation.

This master thesis deals with the software support of one Financial and Property Analysis of Municipalities (FAMA). The co-author of this method is Doctor Petr Toth from the Institute of Public Administration and Regional Development at University of Economics in Prague. The method is supported by Microsoft Access database application and two C++ applications ArisDestiller and Prognoza at present time. The aim of this thesis is to evaluate the present software support of Financial and Property Analysis and implement an alternative solution based on Business Intelligence tools. Chosen part of analysis is implemented in the pilot project using Microsoft SQL Server 2005 environment. The thesis focuses mainly on using integration tools for XML data. The contribution of the thesis is to implement data warehouse, which uses the municipalities‘annual bills in XML format from the database of Ministry of Finance of the Czech Republic. The Financial and Property Analysis method and the current software support are discussed in the first half of this thesis. The other half of the work is dedicated to the Business Intelligence pilot project. Both means of software support are reviewed and compared from various perspectives in the conclusion.

Knowledge discovery from databases is a complex issue involving integration, data preparation, data mining using machine learning methods and visualization of results. The thesis deals with the whole process of knowledge discovery, especially with the issue of data warehousing, where it offers the design and implementation of a specific data warehouse for the company ROI Hunter, a.s. In the field of data mining, the work focuses on the classification and forecasting of the advertising data available from the prepared data warehouse and, in particular, on the decision tree classification. When predicting the development of new ads, emphasis is put on the rationale for the prediction as well as the proposal to adjust the ad settings so that the prediction ends positively and, with a certain likelihood, the ads actually get better results.

In this thesis we try using machine learning techniques to predict final grade of a student in a learning management system on the basis of his behavior during the semester. The aim is to determine the optimal technology for the extraction, treatment and machine learning on data. The whole system would then be implemented as a module that we will be able to plug in the existing system.

The diploma thesis focuses on the analysis of the current state of reporting and data analysis of the ALVAO Service Desk system in the company's internal operation. Based on the findings of deficiencies, a new method of reporting and data analysis on the Microsoft Power BI platform is proposed. The proposal includes the entire Power BI feature cycle from data accessing to sharing.

The master's thesis focuses on the creation of the automatic error cleansing software which clears the errors generated by the ordering system. Based on the error analysis (e.g. their causes and possibilities of their correction) the software enables the automatic error correction without the necessity of any manual action resulting in minimal delay of customers’ orders.

The thesis addresses the issue of developing indicators focusing on measuring human capital, which will serve as a reporting output from the data warehouse. Goal is propose a set of indicators that will be able to cover the overall picture of corporate human resources. I focused mainly on building sets of indicators for measuring the area of human resources and human capital.

Denna rapports frågeställning är: hur lämpar sig psykiatrins data för en datalagerstruktur och inleds med en bakgrund där en litteraturstudie genomförs. Efter detta kommer en metod del och en genomförande del där intervjuer med avdelningschefer, verksamhetschefen, samt en verksamhetsutvecklare på ett svenskt universitetssjukhus psykiatriavdelning beskrivs. Genom observationer och analys av sjukhusets data samt svaren från respondenterna sammanställdes ett resultat som visar emot att detta sjukhus inte har en god grund för en datalagerstruktur, men genom omprioriteringar kan detta förbättras. Resultatet baserades på forskning gjord av Inmon (2005) och fyra av de kategorier som han anser är mest relevanta för en datalagerstruktur, samt insamlad data från universitetssjukhuset. Det framkom även att alla svenska sjukhus verkar ha problem med sina system och att hela svenska vården är i en uppgraderingsfas där det vid en sådan investering bör prioriteras att skapa fungerande datalagerstrukturer för att kunna analysera vilka resultat vården ger. Just nu fattas beslut i blindo och detta kommer inte förändras om inte förändring sker. / This report's question is: how does psychiatry's data fit into a data warehouse structure and starts with a background in which a literature study is carried out. After this, a method part and an implementation part will be described in which interviews with department heads, the operations manager, as well as an operations developer at a Swedish university hospital's psychiatry department are described. Through observations and analysis of the hospital data and the responses of the respondents, a result was compiled which shows that this hospital does not have a good basis for a data warehouse structure, but through re-prioritization this can be improved. The result was based on research done by Inmon (2005) and four of the categories that he considers to be most relevant to a data warehouse structure, as well as data collected from the university hospital. It also emerged that all Swedish hospitals seem to have problems with their systems and that the entire Swedish healthcare system is in an upgrade phase where it should be prioritized in such an investment to create functioning data warehouse structures in order to be able to analyze the results the health care gives. Right now, decisions are being made blindly and this will not change unless change is made.

Customer knowledge plays a vital part in organisations today, particularly in sales and marketing processes, where customers can either be channel partners or final consumers. Managing customer data and/or information across business units, departments, and functions is vital. Frequently, channel partners gather and capture data about downstream customers and consumers that organisations further upstream in the channel require to be incorporated into their information systems in order to allow for management information delivery to their users. In this study, the focus is placed on manufacturing organisations using third party distribution since the flow of information between channel partner organisations in a supply chain (in contrast to the flow of products) provides an important link between organisations and increasingly represents a source of competitive advantage in the marketplace. The purpose of this study is to determine whether there is a significant difference in the use of sales and marketing data marts as management information delivery mechanisms in manufacturing organisations in different industries, particularly the pharmaceuticals and branded consumer products. The case studies presented in this dissertation indicates that there are significant differences between the use of sales and marketing data marts in different manufacturing industries, which can be ascribed to the industry, both directly and indirectly. / Thesis (MIS(Information Science))--University of Pretoria, 2002. / Information Science / MIS / unrestricted