National Repository of Grey Literature 229 records found  previous11 - 20nextend  jump to record: Search took 0.00 seconds. 
Mobile reporting
Irišek, Michael ; Kerol, Valeria (advisor) ; Novotný, Ota (referee)
Primary goal of this Bachelor thesis is to analyse chosen pairs of mobile devices and reporting applications in order to find the most suitable combination for purposes of mobile reporting. This analysis takes place in pursuance of mapping current situation on the market of appropriate mobile applications and for facilitating the choice of suitable mobile reporting solutions for potential customers. For achieving the primary goal, the author used multicriterial selection. Secondary goal is familiarizing the reader with the issues of Business Intelligence, reporting and mobile devices. The global market was analysed on basis of presented knowledge for the purpose of choosing the right combinations for further testing. Furthermore, the thesis determines evaluated criteria later used for testing purposes. Thesis informs about this process and analyses the results, therefore completing its primary goal.
Business Intelligence trends
Meloun, Jaroslav ; Kerol, Valeria (advisor) ; Novotný, Ota (referee)
The main goal and contribution of this Bachelor thesis is to analyse and compare Business Intelligence (BI) solutions according to the actual trends in order to help a potential customer to select a suitable BI solution. Firstly, the minor goals are achieved: the basic theoretical knowledge about BI (definition of BI, a general architecture and components of BI) is provided to a reader, actual BI trends are identified and a current BI market is analysed. Next, the criteria are set and the analysis and the comparison of selected BI solutions are performed. Finally, there is a final evaluation in the form of tables. Also, strengths and weaknesses of each analysed solution are identified based on the performed analysis and the comparison.
Machine learning in the field of Big Data
Šimánek, Michal ; Kerol, Valeria (advisor) ; Novotný, Ota (referee)
This bachelor's thesis devotes to the field of machine learning in Big Data. The main aim is to map and evaluate current situation of machine learning in Big Data, select and compare the most used machine learning libraries in Apache Spark tool and provide guide, how to implement algorithms of selected libraries. Theoretical part consists of explaining concept of Big Data, tools Apache Hadoop and Apache Spark, machine learning and decribes most used machine learning libraries in the Apache Spark tool along with comparsion metrics. Practical part is oriented to implementation of algorithms of selected libraries, writing the guide for implementation and according to outcomes and implementations comparing selected libraries from different views. Contribution of this thesis is to introduce machine learning problematics in Big Data, describe most used machine learning libraries and compare selected libraries with providing guide how to implement their algorithms.
The use of metadata in an environment of Self-Service Business Intelligence
Šebák, Ctibor ; Matějka, Martin (advisor) ; Novotný, Ota (referee)
This bachelor thesis is focused on the use of metadata in an environment of Self-Service Business Intelligence. Metadata are structured data that contain information used to de-scribe other data. They contain information about the origin, purpose, location, content and other properties of said data. The main advantage of the self-service BI tools lies in the fact, that the end user customizes the outputs of said tools (reports, data visualizations, etc.) to his own liking. The aim of this thesis is to briefly explain and define the concept of Self-Service Business Intelligence and the concept of metadata, to describe the purpose and benefits of using business metadata. Furthermore, to explore the possibilities of selected tools in context of metadata, more importantly - business metadata. The main contribution of this work is to reveal the possibilities of working with business metadata for selected tools and its empiric testing.
Comparison of reporting applications for mobile devices
Stejskal, Karel ; Šedivá, Zuzana (advisor) ; Novotný, Ota (referee)
This bachelor thesis focuses on the mobile devices market and the possibilities of their use for presentation of key business data using reporting applications. The goal of the thesis is to provide a comprehensive view of the mobile devices market as well as available reporting applications of commercial suppliers who play a crucial role in this segment. Then compare these applications using a multi-criteria evaluation based on a list of criteria and determine the most suitable application that has received the highest rating in this comparison. The final output is a table of compared applications with the ratings assigned to the individual criteria. The thesis serves as a basic orientation in the mobile reporting applications market. Application comparison results can be a useful source of information for companies planning to integrate them into their enterprise information system.
Pilot implementation of Business Intelligence in a retail company
Savka, Ján ; Novotný, Ota (advisor) ; Matějka, Martin (referee)
The thesis focuses on implementation of Business Intelligence in a small retail company. The aim of the thesis is to design a pilot Business Intelligence solution to support management activities in Lintea, s. r. o. The company is part of Slovak lingerie and underwear retail market since 2004. Business performance measurement is not effectively supported in the company. Rise in the quality level of management activities is the main benefit of the proposed implementation which is achieved by delivering previously inaccessible or laboriously accessible information in an appropriate form. Proposed solution substantially simplifies, accelerates and improves management and decision making activities in the company. Thesis has two parts: theoretical and practical. Theoretical part has two chapters devoted to performance management and BI. Chapter about performance management presents wider aspects of using BI in companies and introduces the Balanced Scorecard method. Chapter about Business Intelligence defines BI, explains its principles, components and basic analytic method of BI - the dimensional modelling which is then applied in the practical part. The theoretical part ends with the description of current situation in the BI market. The practical part starts with the introduction of the company Lintea, s. r. o. followed by the description of its current state and proposal of the business performance measures based on the Balanced Scorecard method. Second chapter of the practical part contains the proposed Business Intelligence solution itself. Individual steps of the Business Intelligence design process are: analysis of prerequisites and requirements, analysis of data sources, dimensional modelling, ETL design, multidimensional data structures design and finally presentation layer design.
Integration of Big Data and data warehouse
Kiška, Vladislav ; Novotný, Ota (advisor) ; Kerol, Valeria (referee)
Master thesis deals with a problem of data integration between Big Data platform and enterprise data warehouse. Main goal of this thesis is to create a complex transfer system to move data from a data warehouse to this platform using a suitable tool for this task. This system should also store and manage all metadata information about previous transfers. Theoretical part focuses on describing concepts of Big Data, brief introduction into their history and presents factors which led to need for this new approach. Next chapters describe main principles and attributes of these technologies and discuss benefits of their implementation within an enterprise. Thesis also describes technologies known as Business Intelligence, their typical use cases and their relation to Big Data. Minor chapter presents main components of Hadoop system and most popular related applications. Practical part of this work consists of implementation of a system to execute and manage transfers from traditional relation database, in this case representing a data warehouse, to cluster of a few computers running a Hadoop system. This part also includes a summary of most used applications to move data into Hadoop and a design of database metadata schema, which is used to manage these transfers and to store transfer metadata.
Using of data mining techniques and principles in the Business Intelligence solution
Štefke, Martin ; Chudán, David (advisor) ; Novotný, Ota (referee)
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.
Social network monitoring as a service to monitor business environment
Filip, Petr ; Jelínek, Ivan (advisor) ; Novotný, Ota (referee)
This project is focused on gathering information about environs of the company presented on the social networks and choosing the right tools to analyze the perception of the firm and its products between the users of the social network. In the first part, the benefits of analization on social network based on the rating metrics gained from the datas of social networks are explained. In the second part the right social network is chosen to analyze and then the proccess of accessing the datas is revealed. The last part of the project is about different political situations in addition of monitoring the traditional medias and complete informational value of the analysation is shown. The result of this whole project is to compare the differences between informational value from the classic medias and the informational valuenof the social networks and eventually whole application for the company.
Application of text mining methods for analysis of users movie reviews
Palatínus, Vojtěch ; Matějka, Martin (advisor) ; Novotný, Ota (referee)
The topic of this thesis is to define the challenges while working with the unstructured data. It focuses, specifically, on a transformation between unstructured and structured data using text mining methods and bringing the closer view on so-called Big Data phenomenon. The goal of this thesis is to introduce problems that occur when working with unstructured data, to show their transformation to structured data format using text mining methods and to perform analysis on user reviews published on the website of The Internet Movie Database from the mined data. The aim of this thesis is to familiarize the reader with the unstructured data and on the example demonstrate how to use text mining methods for mining relevant information from this type of data.

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See also: similar author names
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