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Visualization of Data Quality in Business Intelligence
Pohořelý, Radovan ; Pour, Jan (advisor) ; Zajíc, Ján (referee)
This thesis deals with the area of Business Intelligence and especially the part of data quality. The goal is provide an overview of data quality issue and possible ways the data can be shown to have better and more engaging informative value. Another goal was to make a proposal solution to the visualization of the system state, particularly the section of data quality, at the concrete enterprise. The output of this thesis should provide a quideline for the implementation of the proposed solution.
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Data Governance - The implementation project concept
Kmoch, Václav ; Svatá, Vlasta (advisor) ; Kalina, Jaroslav (referee)
Companies in these days deal with underlying issue that concerns about questions how to manage volume growth of corporate data needed to decision making processes and how to control credibility and relevance of derived information and knowledge. Other questions deal with problem of responsibility and data security that represents potential risk of information outflow. The Data Governance concepts provide comprehensive answer to these questions. However, making a decision on implementing a Data Governance program is usually triggering many other problems like setting up environments, making determination of project scope, allocating capacity of data experts and finding one's way in non-uniform Data Governance concepts offered by various IT vendors. The aim of this thesis is to draw the unified and universal implementation process that helps with setting up DG projects and makes certain conception about how to run these projects step-by-step. The first and the second part of the thesis are dedicated to describe principles, components and tools of Data Governance and also methods of measuring data quality levels. The third part is offering concrete approach for successful implementation of Data Governance conception into corporate data environment.
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Master Data Management, Customer Data Integration and value for business
Rais, Filip ; Novotný, Ota (advisor) ; Slánský, David (referee)
This thesis is focused on Master Data Management (MDM), Customer Data Integration (CDI) area and its main domains. It is also a reference to a various theoretical directions that can be found in this area of expertise. It summarizes main aspects, domains and presents different perspectives to referenced principles. It is an exhaustive background research in area of Master Data Management with emphasis on practical use with references on authors experience and opinions. Secondary focus is directed to the field of business value of Master Data Management initiatives. Thesis presents a thought concept for initiations of MDM project. The reason for such a concept is based on current trend, where companies are struggling to determine actual benefits of MDM initiatives. There is overall accord on the subject of necessity of such initiatives, but the struggle is in area of determining actual measureable impact on company's revenue or profit. Since the MDM initiative is more of an enabling function, rather than direct revenue function, the benefit is less straight forward and therefore harder to determine. This work describes different layers and mapping of business requirements through layers for transparent linkage between enabling functions to revenue generating ones. The emphasis is given to financial benefit calculation, measurability and responsibility of business and IT departments. To underline certain conclusions thesis also presents real world interviews with possible stakeholders of MDM initiative within the company. These representatives were selected as key drivers for such an initiative. Interviews map their recognition of MDM and related terms. It also focus on their reasons and expectations from MDM. The representatives were also selected to equally represent business and IT departments, which presents interesting clash of views and expectations.
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Data Quality And Tools For Its Management
Tezzelová, Jana ; Pour, Jan (advisor) ; Polášek, Marek (referee)
This diploma thesis deals with data quality, with emphasis on issues of management and on tools which were developed for solving data quality issues. The goal of this work is to summarize knowledge about data quality problems which includes its evaluation, management, description of key problems in data and possibilities of their solutions. The aims of this thesis are among others also analysis of market of software tools for support and management of data quality and mainly comparison of functionalities and possibilities of several of those tools. This work is split into two consequential parts. The first theoretical part is focusing on opening to problems of data quality and mainly data quality management, including identification of main steps for successful management. The second practical part is focusing on the market with data quality tools, especially its characteristics, segmentation, evolution, current state and expectable trends. The important section of this part is also practical comparison of features and evaluation of the work with several data quality tools. This work aims to be beneficial for all the audience interested in data quality problems, especially its management and supporting technology. Thanks to focusing on data quality tools market and tools comparison this work could be also useful guide for companies which are currently choosing the proper tool for introducing the data quality. Regarding this work focus the readers are expected to have at least basic orientation in Business Intelligence.
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Data Quality, Data intagrity and Data Consolidation in BI
Smolík, Ondřej ; Pour, Jan (advisor) ; Zajíc, Ján (referee)
This thesis fights with the data quality in business intelligence. We present basic principles for building data warehouse to achieve the highest data quality. We also present some data clearing methods as deviation detection or name-address clearing. This work also deals with origin of erroneous data and prevention of their generation. In second part of this thesis we show presented methods and principles on real example of data warehouse and we suggest how to get sales data from our business partners or customers.
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Data quality, data integrity and consolidation of data in BI
Dražil, Michal ; Pour, Jan (advisor) ; Zajíc, Ján (referee)
This thesis deals with the areas of enterprise data quality, data integrity and data consolidation from the perspective of Business Intelligence (BI), which is currently experiencing significant growth. The aim of this thesis is to provide a comprehensive view of the data quality in terms of BI, to analyze problems in the area of data quality control and to propose options to address them. Moreover, the thesis aims to analyze and assess the features of specialized software tools for data quality. Last but not least aim of this thesis is to identify the critical success factors in the field of data quality in CRM and BI projects. The thesis is divided into two parts. The first (theoretical) part deals with data quality, data integrity and consolidation of data in relation to BI trying to identify key issues, which are related to these areas. The second (practical) part of the thesis deals at first with the features of software tools for data quality and offers their fundamental summary as well as the tools breakdown. This part also provides basic comparison of the few selected software products specialized at the corporate data quality assurance. The practical part hereafter describes addressing the data quality within the specific BI/CRM project conducted by Clever Decision Ltd. This thesis is intended primarily for BI and data quality experts, as well as the others who are interested in these disciplines. The main contribution of this thesis is that it provides comprehensive view not only of data quality itself, but also deals with the issues that are directly related to the corporate data quality assurance. This thesis can serve as a sort of guidance for one of the first implementation phases in the BI projects, which deals with the data integration, data consolidation and solving problems in the area of data quality.
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Data Quality and Effective Use of Registers of State Administration
Rut, Lukáš ; Chlapek, Dušan (advisor) ; Jankech, Pavel (referee)
This diploma thesis deals with registers of state administration in term of data quality. The main objective is to analyze the ways how to evaluate data quality and to apply appropriate method to data in business register. Analysis of possibilities of data cleansing and data quality improving and proposal of solution of found inaccuracy in business register is another objective. The last goal of this paper is to analyze approaches how to set identifier of persons and to choose suitable key for identification of persons in registers of state administration. The thesis is divided into several parts. The first one includes introduction into the sphere of registers of state administration. It closely analyzes several selected registers especially in terms of which data contain and how they are updated. Description of legislation changes, which will come into operation in the middle of year 2010, is great contribution of this part. Special attention is dedicated to the impact of these changes from data quality point of view. Next part deals with problems of legal and physical entities identifiers. This section contains possible solution how to identify entities in data from registers. Third part analyzes ways how to determine data quality. Method called data profiling is closely described and applied to extensive data quality analysis of business register. Correct metadata and information about incorrect data are the outputs of this analysis. The last chapter deals with possibilities how to solve data quality problems. There are proposed and compared three variations of solution. The paper as a whole represents compact material how to solve problems with effective using of data contained in registers of state administration. Nevertheless, proposed solutions and described approaches can be used in many other projects which deal with data quality.
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The influence of etalons on the data qualitiy in companies
Bukovský, Radim ; Slánský, David (advisor) ; Pour, Jan (referee)
This thesis is dedicated to all persons who are interested in information of the data quality (especially the Data Cleansing). Everyone who wants to get to know more about etalons, the essential part of the data quality, is welcomed. The insight into everyday activities of people working not only on creating and administrating of etalons but also implementing them on particular projects is prepared for everyone. The reader will also gain detailed knowledge of how etalons could help companies with decreasing their costs and how etalons can make better impression to company's clients through the data quality.
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Data Governance Implementing Method
Slouková, Anna ; Slánský, David (advisor) ; Pour, Jan (referee)
This thesis refers to Data Governance issue and the way of implementing this program. It is logically devided into two parts -- theoretical and practical one. The teoretical part represented by first chapter summarises actual findings about the Data Governance program, it explains what is hidden behind the term Data Governance, cause for Data Governance initiatives emergence, it itemizes particular parts of which the program is composed and basic, mostly software tools, that are necessary for successful program run. Practical part consists of second and third chapter. The second chapter contains enumeration of various types of outputs that grow up either during the implementation of program or in its run itself. It categorizes and deals in detail with processes and activities, organizational structure of the program, dokuments, used metrics and KPIs and IS/IT tools. Third chapter describes the process of implementing the program into an enterprise in detail. It is devided into four consequential phases -- assessment of current state, design, implementation and run of the program. In every chapter, there are inputs, outputs, detailed decomposition into particular activities with references to document tepmlates that are used during theese activities, risks and resources introduced. In two attachments of this thesis, there are two helpful documents -- general document teplate and teplate of a role description -- that serve to better implementation of Data Governance program.
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Data Quality Metrics
Sýkorová, Veronika ; Slánský, David (advisor) ; Pour, Jan (referee)
The aim of the thesis is to prove measurability of the Data Quality which is a relatively subjective measure and thus is difficult to measure. In doing this various aspects of measuring the quality of data are analyzed and a Complex Data Quality Monitoring System is introduced with the aim to provide a concept for measuring/monitoring the overall Data Quality in an organization. The system is built on a metrics hierarchy decomposed into particular detailed metrics, dimensions enabling multidimensional analyses of the metrics, and processes being measured by the metrics. The first part of the thesis (Chapter 2 and Chapter 3) is focused on dealing with Data Quality, i.e. provides various definitions of Data Quality, gives reasoning for the importance of Data Quality in a company, and presents some of the most common tools and solutions that target to managing Data Quality in an organization. The second part of the thesis (Chapter 4 and Chapter 5) builds on the previous part and leads into measuring Data Quality using metrics, i.e. contains definition and purpose of Data Quality Metrics, places them into the multidimensional context (dimensions, hierarchies) and states five possible decompositions of Data Quality metrics into detail. The third part of the thesis (Chapter 6) contains the proposed Complex Data Quality Monitoring System including description of Data Quality Management related dimensions and processes, and most importantly detailed definition of bottom-level metrics used for calculation of the overall Data Quality.
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