El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado. / The microfinance sector has a strategic role since they facilitate integration and development of all social classes to sustained economic growth. In this way the actual point is the exponential growth of data, resulting from transactions and operations carried out with these companies on a daily basis, becomes imminent. Appropriate management of this data is therefore necessary because, otherwise, it will result in a competitive disadvantage due to the lack of valuable and quality information for decision-making and process improvement. The Master Data Management (MDM) give a new way in the Data management, reducing the gap between the business perspectives versus the technology perspective In this regard, it is important that the organization have the ability to implement a data management model for Master Data Management. This paper proposes a Master Data management maturity model for microfinance sector, which frames a series of formal requirements and criteria providing an objective diagnosis with the aim of improving processes until entities reach desired maturity levels. This model was implemented based on the information of Peruvian microfinance organizations. Finally, after validation of the proposed model, it was evidenced that it serves as a means for identifying the maturity level to help in the successful of initiative for Master Data management projects. / Revisión por pares

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.

Connectivity provided by technology and liberation of trade have led to a globalization of organizations, affecting supply chains to expand in complexity. As a result, many organizations today have challenges of managing information in a consistent manner throughout a complex system environment. This study aims to identify the most valuable attributes of a solution for managing master data, in an efficient and consistent manner, across an extended and complex supply chain. Master data, such as products, customers and suppliers, can be defined as valuable core business information, since it is vital for supporting business operations. A requirements elicitation was performed, including interviews conducted internally with employees at IFS and externally with customers. Furthermore, a requirements analysis resulted in a specification of requirements including the most desirable attributes of a future Master Data Management (MDM) solution. Five main themes of the attributes were identified; architecture, availability and integration, governance, user interface and lifecycle management. The study contributes to the area of research, by identifying challenges and valuable attributes to consider when developing or investing in a solution for MDM.

El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado. / Microfinance has undergone a great growth in the last years, bringing consequently the significant increase of the data of the transactions and daily operations, manual processes of cleaning, complexity in IT projects and, in comparison with the traditional bank, a less amount of resources. For this reason, the model must allow the master data to have maintenance processes that reduce manual cleaning activities and contribute to the implementation of technology projects in an agile manner. On the other hand, the research seeks to combine a basic pillar such as Master Data Management (MDM) for the analysis of information with the lean approach, already used in the industry for the operational cost and additionally an evaluation measure prior to this process obtaining the state of the capabilities in the organization. In this way, the result will be that the organization can be previously evaluated and quickly identify which points should be improved to achieve the implementation of MDM initiatives. Likewise, within the research it is concluded that the Peruvian microfinance sector is prepared for the implementation of master data management with a 'proactive' maturity level of 3.46 points.

This thesis deals with the Master Data Management (MDM), specifically its implementation. The main objectives are to analyze and capture the general approaches of MDM implementation including best practices, describe and evaluate the implementation of MDM project using Microsoft SQL Server 2008 R2 Master Data Services (MDS) realized in the Czech environment and on the basis of the above theoretical background, experiences of implemented project and available technical literature create a general procedure for implementation of the MDS tool. To achieve objectives above are used these procedures: exploration of information resources (printed, electronic and personal appointments with consultants of Clever Decision), cooperation on project realized by Clever Decision and analysis of tool Microsoft SQL Server 2008 R2 Master Data Services. Contributions of this work are practically same as its goals. The main contribution is creation of a general procedure for implementation of the MDS tool. The thesis is divided into two parts. The first (theoretically oriented) part deals with basic concepts (including definition against other systems), architecture, implementing styles, market trends and best practices. The second (practically oriented) part deals at first with implementation of realized MDS project and hereafter describes a general procedure for implementation of the MDS tool.

El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado. / The microfinance sector has a strategic role since they facilitate integration and development of all social classes to sustained economic growth. In this way the actual point is the exponential growth of data, resulting from transactions and operations carried out with these companies on a daily basis, becomes imminent. Appropriate management of this data is therefore necessary because, otherwise, it will result in a competitive disadvantage due to the lack of valuable and quality information for decision-making and process improvement. The Master Data Management (MDM) give a new way in the Data management, reducing the gap between the business perspectives versus the technology perspective In this regard, it is important that the organization have the ability to implement a data management model for Master Data Management. This paper proposes a Master Data management maturity model for microfinance sector, which frames a series of formal requirements and criteria providing an objective diagnosis with the aim of improving processes until entities reach desired maturity levels. This model was implemented based on the information of Peruvian microfinance organizations. Finally, after validation of the proposed model, it was evidenced that it serves as a means for identifying the maturity level to help in the successful of initiative for Master Data management projects. / Revisión por pares

Product Information Management (PIM) is a field that deals with the product master data management and combines into one base the experience and the principles of data integration and data quality. Product Information Management merges the specific attributes of products across all channels in the supply chain. By unification, centralization and standardization of product information into one platform, quality and timely information with added value can be achieved. The goal of the theoretical part of the thesis is to construct a picture of the PIM, to place the PIM into a broader context, to define and describe various parts of the PIM solution, to describe the main differences in characteristics between the product data and data about clients and to summarize the available information on the administration and management of knowledge bases of the PIM data quality relevant for solving practical problems. The practical part of the thesis focuses on designing the structure, the content and the method of filling the knowledge base of the Product Information Management solution in the environment of the DataFlux software tools from SAS Institute. The practical part of the thesis further incorporates the analysis of the real product data, the design of definitions and objects of the knowledge base, the creation of a reference database and the testing of the knowledge base with the help of specially designed web services.

This thesis is focused on Master Data Management of Product Data. At present, most publications on the topic of MDM take into account customer data, and a very limited number of sources focus solely on product data. Some resources actually do attempt to cover MDM in full-depth. Even those publications are typically are very customer oriented. The lack of Product MDM oriented literature became one of the motivations for this thesis. Another motivation was to outline and analyze specifics of Product MDM in context of its implementation and software requirements for a vendor of MDM application software. For this I chose to create and describe a methodology for implementing MDM of product data. The methodology was derived from personal experience on projects focused on MDM of customer data, which was applied on findings from the theoretical part of this thesis. By analyzing product data characteristics and their impacts on MDM implementation as well as their requirements for application software, this thesis helps vendors of Customer MDM to understand the challenges of Product MDM and therefore to embark onto the product data MDM domain. Moreover this thesis can also serve as an information resource for enterprises considering adopting MDM of product data into their infrastructure.

In current information systems the requirement to integrate disparate applications into cohesive package is greatly accented. While well-established technologies facilitating functional and comunicational integration (ESB, message brokes, web services) already exist, tools and methodologies for continuous integration of disparate data sources on enterprise-wide level are still in development. Master Data Management (MDM) is a major approach in the area of data integration and referrential data management in particular. It encompasses the referrential data integration, data quality management and referrential data consolidation, metadata management, master data ownership, principle of accountability for master data and processes related to referrential data management. Thesis is focused on technological aspects of MDM implementation realized via introduction of centrallized repository for master data -- Master Data Integration Hub (MDI Hub). MDI Hub is an application which enables the integration and consolidation of referrential data stored in disparate systems and applications based on predefined workflows. It also handles the master data propagation back to source systems and provides services like dictionaries management and data quality monitoring. Thesis objective is to cover design and implementation aspects of MDI Hub, which forms the application part of MDM. In introduction the motivation for referrential data consolidation is discussed and list of techniques used in MDI Hub solution development is presented. The main part of thesis proposes the design of MDI Hub referrential architecture and suggests the activities performed in process of MDI Hub implementation. Thesis is based on information gained from specialized publications, on knowledge gathererd by delivering projects with companies Adastra and Ataccama and on co-workers know-how and experience. Most important contribution of thesis is comprehensive view on MDI Hub design and MDI Hub referrential architecture proposal. MDI Hub referrential architecture can serve as basis for particular MDI Hub implementation.

Stora företag har olika avdelningar där informationen från dessa måste hanteras. Master Data Management(MDM) är ett informationshanteringssystem för att hantera information från olika källor. En MDM-implementation sker med en entitet i taget. Arbetets problemställning är att rekommendera nästa entitet att inkludera i MDM-implementationen hos Scania samt vilken leverantör som passar till implementationen. En rekommendation av entitet framställs av material från Scania och intervjuer med anställda på Scania. Rekommendationen av leverantör framställs från material från leverantörer och intervjuer med leverantörerna. Entiteten som rekommenderas är produkt som individ för att informationen i området har behov av förbättrad hantering och entiteten är nära kärnverksamheten. Orchestra Networks är leverantören som rekommenderas för att de ligger i framkant inom MDM, de är nischade mot området och är starka inom produktinformation. / Enterprises has different departments and the information from them needs management. Master Data Management(MDM) is an information handling system for handling information from different sources.  One entity at the time is implemented to MDM. The work's problem is to recommend the next entity to include in the MDM implementation at Scania as well as which provider fits the implementation. A recommendation of entity is prepared from materials provided by Scania and interviews with employees at Scania. A recommendation of provider is prepared from materials from the providers and interviews with the providers. The recommended entity is product as individual because information in the area needs improved management. Orchestra Networks is the recommended supplier because they are a leader among the MDM providers, they are specialised in the area and they are strong in the product information area.