The Diploma thesis discusses Balanced scorecard and Business intelligence solution on universities. Solution is systematically divided into two main units, each with its chapters. First unit focuses on theory of Balanced scorecard and Business Intelligence. There are shown four basic perspectives of the Balanced scorecard and the basics are further enhanced by modifications, focusing on academic environment. Second chapter introduces the basic information readers needs to continue into the most important part of this work, which is pilot implementation of Business Intelligence at the University in Prague. Second unit deals with practical implementation of theoretical knowledge, gained in first unit. The following is specification of University in Prague with proposal of Balanced scorecard for the University in Prague. This is base fo further work, where is implemented pilot Business intelligence solution with basic reports.

This diploma thesis presents Big Data technologies and their possible use cases and applications. Theoretical part is initially focused on definition of term Big Data and afterwards is focused on Big Data technology, particularly on Hadoop framework. There are described principles of Hadoop, such as distributed storage and data processing, and its individual components. Furthermore are presented the largest vendors of Big Data technologies. At the end of this part of the thesis are described possible use cases of Big Data technologies and also some case studies. The practical part describes implementation of demo example of Big Data technologies and it is divided into two chapters. The first chapter of the practical part deals with conceptual design of demo example, used products and architecture of the solution. Afterwards, implementation of the demo example is described in the second chapter, from preparation of demo environment to creation of applications. Goals of this thesis are description and characteristics of Big Data, presentation of the largest vendors and their Big Data products, description of possible use cases of Big Data technologies and especially implementation of demo example in Big Data tools from IBM.

The first aim of this thesis is map the Microsoft development tools for business intelligence systems. This goal devide the tools for develop BI into two groups: tools for traditional BI systems and tools for self-service BI systems. The second aim of this thesis is a critical evaluation of approaches based on the criteria and scenarios focuse on selected business areas. This thesis answers the question if some of the approaches is a better solution for business intelligence systems, or whether one approach is more suitable for business intelligence solutions to some business areas.

This thesis is focused on the design of Business Intelligence solution to the logistics sector. Its main goal is to enable the unnamed central-bohemian company, which deals with truck road transportation, to follow up and evaluate its data better. The theoretical part is focused on the basic principles of Business Intelligence and on the analysis of current market situation. The next section is dedicated to the specifics of this problematic in the logistics field. The practical part deals with the design of Business Intelligence solution to the concrete company. The analysis of company preparedness for Business Intelligence and the specification of requirements on its solution precede the resultant reporting tool. There is the unification of company's data in the form of data warehouse and the design of individual indexes and dimensions, from whose point of view data will be monitored. The main benefit of this thesis is resultant solution in the form of reporting tool, which can company, that is not familiar with the problematic of Business Intelligence, use as its future advantage.

Diploma thesis focuses on in-memory data processing, its use in reporting and Business Intelligence (BI) in general. The main goal of the theoretical part is to introduce the in memory principles, highlight the differences from hard drive data processing and overview possible implementations of in-memory technology in BI solution. The output of this section is an analysis of advantages and disadvantages of in-memory solutions in various perspectives. The practical part of the thesis consists of the performance benchmark that compares the performance of data processing using the in-memory principles and conventional hard drive methods. The performance comparison is realized in the reporting tools environment, QlikView for in-memory approach and Reporting Services for hard drive based method. Several data sets are used for testing in both mentioned tools. End of the chapter provides the assessment of testing results and discusses the strengths and weaknesses of both principles of data processing. The conclusion of this work discusses the advantages and disadvantages of in-memory data processing and defines the key questions that company management should ask before investing in innovation of the present BI solution. Moreover the conclusion contains recommendations for possible further follow-up work.

This thesis deals with the Microsoft's self-service business intelligence tools and it's used for eCommerce. The main goal of this work is to analyze and design metrics and applications for effective management of eCommerce using PowerPivot and Power View. Metrics are based on balanced scorecard approach and applications are based on MBI reference model. This thesis is supposed to help eCommerce managers and administrators to implement a custom self-service business intelligence solution.

The main objective of the diploma thesis called "Analysis and design of BI Reporting and Dashboards Survey" is to analyze the main principles of Business Intelligence and Corporate Performance Management approach with a focus on performance reporting and dashboards, and to design a survey form for BI Reporting and Dashboards Survey which will focus on the current state of the reporting and dashboards in European enterprises. The final design of the market survey form is based on the identified key areas of the topic and is created by using the basic principles of statistics which help to compose successful market surveys. It represents the main input for the conduct of the quantitative market survey planned to be realized in the summer of 2014. The first part of the diploma thesis represents the theoretical baseline for the analysis of the key areas of the survey's content. This part includes introduction to the BI and CPM principles (chapter 2) followed by the identification and definition of key elements of successful BI reporting and dashboards (chapter 3). The last chapter of this part (chapter 4) summarizes the key principles of statistics leading to beneficial composition of market surveys. The second, practical part of the diploma thesis (chapter 5), presents the overall design of the BI Reporting and Dashboards Survey. This design includes scope, objectives of the survey, profile of respondents, and specification of the question form with predefined range of possible answers to each individual question. The final design of the question form is also available in Appendix 1 in MS Excel file. This diploma thesis emphasizes the importance of the effective performance reporting and the beneficial use of dashboards in organizations and outlines the key areas of those topics which business representatives should focus on. Another benefit of this thesis is the prepared question form itself which might bring interesting and valuable findings about the current state of BI reporting and dashboards implemented and used among the European countries.

This thesis focuses on reporting and problems which are related to it. The main goal is to define the principles of effective report design and its usage and also define rules for choice of appropriate and useful content. This principles and rules are result of detailed analysis based on problems with reports. Contemporary theses are above all focused on technical and visual aspects of reporting. This thesis the contemporary field of view extends by aspect of content. It also focuses on mechanisms, which are important in reporting systems and setting of these mechanisms. The thesis consists of five related parts. The first two chapters define a theoretical basis, while first chapter is dedicated to principles of Business Intelligence and second chapter focuses on reports. Next chapter contains the analysis of problems with reports and defines their fundamental causes. Fourth chapter defines principles of effective report design and the last chapter confronts conclusions of author of this thesis with practice.

The thesis focuses on requirements, which must be established when business intelligence is chosen, from user point of view. Business intelligence je decision support system and it is very important, that system must be ease of use and provide expected information for analyst and managers. During the process of choosing the software, they are the one, who provide requirements and expectation of the system. The thesis focuses on mapping those requirements and their importance using survey among analyst and managers, who uses business intelligence or want to use it.

The thesis describes implementation of Business Intelligence solution in mid-sized company which produces and sells animal nutrition products. Currently the company uses basic tools for reporting, mostly Excel application. Considering the data growth, that solution is about not to be sufficient. In the first part of the thesis, the Business Intelligence principals are introduced to the reader, so one is provided with enough knowledge to understand the issue of data processing, transforming and storing. Basics of data visualization used for decision making in the company are introduced as well. At the end of the chapter, there is a list of general rules for creating a dashboard. The secord part describes the Trouw Nutrition Biofaktory s.r.o. company, where the implementation of new Business Intelligence solution is going to take place. The reader will learn about the company size, structure and history. The last part contains a new procedure how to process data for reporting purposes. The design includes data loading to MS SQL 2012 database server and further processing for analytical purposes. In addition, OLAP cube is created as well as three monthly dashboards.