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Analýza BI dat pomocí geografického systému. / Analysis of BI data using geographic information systemJurečka, Jan January 2011 (has links)
The topic of the current Master's thesis is Business Intelligence's data presentation using maps. Through integrating BI and geographic information systems a new discipline is emerging - Location Intelligence. The main goal of this thesis is to highlight and analyse reporting possibilities of the BI tools in the framework of maps. The theoretical part of this paper is dedicated to the foundation and principles of geographic information systems and their intersection with BI, where such field as Location Intelligence is being created. In the practical part of the thesis the BI tools IBM Cognos and Oracle BI are compared. The comparison is based on the following criteria: field of implementation, visualization, map external sources and performance. The evaluating criteria are defined in the beginning of the practical part as well as the evaluation method. The methods of analysis and information collecting were used to extract and revise the knowledge from specific electronic and printed sources in Czech or English. Sources for the practical part origin from my technical knowledge of the field of BI, as well as practical experience with implementation of map sources as a feature of Business Intelligence. Statistical methods are used for evaluation of the criteria results. The practical and theoretical value of the thesis lies in creating the lucid comparison of implementation of the map sources into the selected BI tools and options for reporting or visualization of BI data over map. Apart from comparison the framework for implementation of maps into the selected BI tools is established in the above mentioned work.
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Využití geolokace v oblasti autopojištění / Use of geolocation in car insurance productsČerná, Kristýna January 2013 (has links)
This thesis focuses on the Geolocation, Marketing and Insurance area. The main objective is to create definition of car insurance product for the market of Czech Republic, which will use the data gained from geolocation for the premiums adjustment. The minor objective of this thesis is to propose appropriate marketing strategy, which could be used while launching product on Czech market. Thesis is divided into theoretical and practical part. Theoretical part describes principles of geolocation, provides basic information about several specific car insurance products from Czech Republic and abroad markets. The last part of theoretical section is focused on marketing topic. Practical part of this thesis consists of car insurance product specification. Proposal for optimal marketing strategy and targeted customer groups is also included. The main output of this thesis is definition of new car insurance product, which is currently not available on Czech market. This specification could be used by Products specialists from Czech insurance companies as basis for definition of new car insurance product for Czech market.
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Implementace BI v oblasti geolokačních dat / Implementation of BI in the field of geolocation dataRosenberger, Tomáš January 2014 (has links)
The thesis deals with the theoretical and practical aspects of implementation of Business Intelligence in a field of geo-location data with emphasis on the design and implementation of data architecture and the development of dynamic dashboards. The whole issue is described on the development of a tool for the analysis of geo-location data, on which the author participated with other members of the Competence Center Retail Analytics - Ondrej Funiok, Vilem Kalus and Martin Matejka. The first part of the thesis describes the theoretical bases of Business and Location Intelligence, which is followed by a description of the basic tasks of working with geo-location data - data storage in relational database management systems, data processing by map servers and data presentation. Individual tasks are described with practical examples and use software tools to support these tasks. The next section presents the project of development tool for the analysis of geo-location data that is created in the Retail Analytics Competence Center at the University of Economics, Prague. The second part of the thesis describes the design and implementation of the data architecture of developed tool, which is followed by a description of the frontend portion of the tool consisting of the implementation of a library for creating dynamic Dashboards to present geo-location data.
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Implementace nástroje pro analýzu dat o pohybu osob / Implementation of a tool for human movement data analysisMatějka, Martin January 2014 (has links)
The aim of this thesis is to provide an insight into theoretical and practical aspects of an analytical tool developed by Ondřej Funiok, Vilém Kalus, Tomáš Rosenberger and Martin Matějka at the University of Economics in Prague. The goal was to develop a tool which could be used for an analysis of human movement within a given place (e.g. retail store) and which could leverage traditional customers' data like age, gender or profession in order to enrich outcomes of conducted analysis, as well as provide a new segmentation of these customers based on their movement. Given that, one of the possible scenarios is that marketers would be able to finely-target their campaigns and use the space more effectively. The thesis contains a short introduction to Location Intelligence as a category of systems which the developed tool belongs to. Further a research of existing theses, articles etc., as well as already available products is conducted. Since a documentation of web services' application interface has proved to be an important aspect of the development, a research and comparison of supporting tools follows. Fourth and fifth chapters are of rather practical nature -- the first of them is about an overall design and architecture of the developed tool, while the second one describes the used application interface and its documentation in detail together with the most important aspects of a backend component -- so called ,,GA-Server``.
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Využití mapových podkladů při řešení reportingu / Use of maps in reportingHuňa, Tomáš January 2011 (has links)
The main objective of this thesis is to describe working with spatial data and their use in reports. The author focuses mainly on the MS SQL Server 2008 R2 platform. The first part deals with theoretical foundations. Defines the concept of Location Intelligence and describes its history to the present. It also addresses the benefits of Location Intelligence in various sectors and the relationship with Business Intelligence. Further theoretical part goes on to describe both spatial data at a general level and at the level of MS SQL Server 2008 R2. In addition, it described the use of ESRI Shapefile files and work with these files. From the description of spatial data author goes on to use reporting tools in Microsoft - SQL Server Reporting Services and Report Builder. Possible forms of map visualization and a detailed description of the settings are at the end of the theoretical part. The second part is focused on solving practical problems. Tools that are described in the theoretical part, are used to create report examples that the author at the beginning of this section set out to create.
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Lokační data se zaměřením na oblast retailu / Spatial data for retail businessKalus, Vilém January 2014 (has links)
The specialization of the final master thesis is theory and a practical view of Location Intelligence. The author is writing about specific parts of development of the application which is focused on analysis of consumer's behaviour for managers of retail businesses focused on customer's satisfaction. The application is a new way of researching consumer's behaviour. Spatial data is connected with the subject of research -- analysis of the movement of consumers in retail stores. The application is a practical tool for better targeting for managers or marketing specialists. The app was developed by four researcher Martin Matějka, Tomáš Rosenberger, Vilém Kalus (three diploma researchers) and Ondřej Funiok. The Main goal of the final thesis was to describe the application from the business point of view and to design layout of the user interface. The business model helped us to specify the application from the business point of view. We reached the main goal with research articles of Location Intelligence. The thesis contains theory basis of informatics and geo-informatics field, Business Intelligence, Location Intelligence and selected business models. The practical part of the thesis is composed of integrating application to the business model, functionality description. From functionality description we designed the user interface. The practical part closes with the use case of application in Vysoká škola ekonomická v Praze. Benefits of the thesis are in development of real, new application for future commercial use. Contribution to the theory of Location Intelligence and analytical solution of development of user interface.
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Retail District Evolution: An Exploration of Retail Structure and Diversity, a Case Study in Denton, TexasBova, Joshua Paul 08 1900 (has links)
It is well established that national retail chains impact small, single location retail businesses in terms of revenue generation, retail structure, retail type diversity, and location. This study examines the retail structure and diversity of five retail districts in the City of Denton, Texas. The analysis focuses on one central business district (CBD), one traditional retail strip center (University Drive, also known as US HWY 380), one special retail district (Fry Street District), one traditional enclosed shopping mall and associated development (Golden Triangle Mall), and one power retail center (Denton Crossing). The empirical foundation for the investigation is a historical business database covering years 1997 to 2010, obtained from Info Group's Reference USA. This Reference USA database includes location, industry, and status (single versus chain location) information for each business. Retail diversity and evenness were measured for each of the five retail districts using the Simpson's Diversity Index and the Simpsons Measure of Evenness, leading to specification of the differences that exist in retail structure and diversity among the districts. Golden Triangle Mall and Denton Crossing were primarily chain location in composition while Fry Street District, the CBD, and University Drive were primarily single location in composition. Across all years, the single versus chain status of the local business communities did not substantially change within any of the districts. The Fry Street District exhibited the most change in diversity as well as the lowest overall diversity among the retail districts, followed by University Drive and Golden Triangle Mall. The CBD did not experience any major change in retail type diversity. However, all retail districts experienced major changes in retail evenness. Overall for the city, single location retail businesses accounted for the majority of all the retail businesses, however, chain locations employed more people. In total, these findings indicate that the development of retail districts composed primarily of chain location retailer's affects retail district diversity and evenness but not retail structure.
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<strong>TOWARDS A TRANSDISCIPLINARY CYBER FORENSICS GEO-CONTEXTUALIZATION FRAMEWORK</strong>Mohammad Meraj Mirza (16635918) 04 August 2023 (has links)
<p>Technological advances have a profound impact on people and the world in which they live. People use a wide range of smart devices, such as the Internet of Things (IoT), smartphones, and wearable devices, on a regular basis, all of which store and use location data. With this explosion of technology, these devices have been playing an essential role in digital forensics and crime investigations. Digital forensic professionals have become more able to acquire and assess various types of data and locations; therefore, location data has become essential for responders, practitioners, and digital investigators dealing with digital forensic cases that rely heavily on digital devices that collect data about their users. It is very beneficial and critical when performing any digital/cyber forensic investigation to consider answering the six Ws questions (i.e., who, what, when, where, why, and how) by using location data recovered from digital devices, such as where the suspect was at the time of the crime or the deviant act. Therefore, they could convict a suspect or help prove their innocence. However, many digital forensic standards, guidelines, tools, and even the National Institute of Standards and Technology (NIST) Cyber Security Personnel Framework (NICE) lack full coverage of what location data can be, how to use such data effectively, and how to perform spatial analysis. Although current digital forensic frameworks recognize the importance of location data, only a limited number of data sources (e.g., GPS) are considered sources of location in these digital forensic frameworks. Moreover, most digital forensic frameworks and tools have yet to introduce geo-contextualization techniques and spatial analysis into the digital forensic process, which may aid digital forensic investigations and provide more information for decision-making. As a result, significant gaps in the digital forensics community are still influenced by a lack of understanding of how to properly curate geodata. Therefore, this research was conducted to develop a transdisciplinary framework to deal with the limitations of previous work and explore opportunities to deal with geodata recovered from digital evidence by improving the way of maintaining geodata and getting the best value from them using an iPhone case study. The findings of this study demonstrated the potential value of geodata in digital disciplinary investigations when using the created transdisciplinary framework. Moreover, the findings discuss the implications for digital spatial analytical techniques and multi-intelligence domains, including location intelligence and open-source intelligence, that aid investigators and generate an exceptional understanding of device users' spatial, temporal, and spatial-temporal patterns.</p>
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