Submitted by João Gabriel Saraceni Lima da Silva (joaosaraceni@id.uff.br) on 2018-03-28T14:50:00Z No. of bitstreams: 1 Joao Saraceni Dissertacao Revisado Banca _V04.pdf: 1375797 bytes, checksum: 36d698762a610b673b13e6a26444a31c (MD5) / Approved for entry into archive by Debora Nunes Ferreira (debora.nunes@fgv.br) on 2018-04-02T17:28:16Z (GMT) No. of bitstreams: 1 Joao Saraceni Dissertacao Revisado Banca _V04.pdf: 1375797 bytes, checksum: 36d698762a610b673b13e6a26444a31c (MD5) / Approved for entry into archive by Suzane Guimarães (suzane.guimaraes@fgv.br) on 2018-04-02T17:45:56Z (GMT) No. of bitstreams: 1 Joao Saraceni Dissertacao Revisado Banca _V04.pdf: 1375797 bytes, checksum: 36d698762a610b673b13e6a26444a31c (MD5) / Made available in DSpace on 2018-04-02T17:45:56Z (GMT). No. of bitstreams: 1 Joao Saraceni Dissertacao Revisado Banca _V04.pdf: 1375797 bytes, checksum: 36d698762a610b673b13e6a26444a31c (MD5) Previous issue date: 2018-02-28 / A diversificação das fontes de dados utilizadas em processos decisórios nas organizações é um dos elementos que fundamentam o conceito de big data, apontado como o futuro das aplicações de Inteligência Analítica. O desafio das organizações em trabalhar com dados não estruturados e dados externos torna-se importante para as que desejam evoluir suas iniciativas de Inteligência Analítica. A partir da revisão de literatura e entrevistas com profissionais que atuam neste campo, este trabalho explora quais as principais iniciativas para obtenção de novas fontes de dados em sistemas de informação de Inteligência Analítica. A abordagem metodológica utilizada foi o estudo de caso múltiplo. A pesquisa utilizou como perspectiva de análise a Teoria da Capacidade Absortiva, que oferece elementos para avaliar como a empresa obtém informações externas a ela e as utiliza no contexto organizacional, gerando valor a seu negócio. São discutidos os principais desafios para a diversificação das fontes de dados, que pode se dar em função da complexidade de diferentes tecnologias, fornecedores, integração de dados, entre outros fatores. Os resultados são apresentados explorando os constructos de Aquisição, Assimilação, Transformação e Utilização, presentes na teoria da Capacidade Absortiva, aplicado à diversificação das fontes de dados nas organizações. Foi possível notar que existem diferentes níveis de utilização de dados externos nas organizações, bem como diferentes arranjos organizacionais para consumir dados externos. As diferentes formas de consumir dados externos causam impacto na forma de alocação de investimentos, governança de dados, cultura organizacional, relacionada ao uso do dado e, por fim, na maturidade do uso de dados externos de forma sistêmica na organização. / The variety of data sources applied into decision-making processes in organizations is one of the factors that defines the concept of big data, indicated as the future of Business Intelligence & Analytics applications. Handle with not structured and/or external data diversifying data sources became important to organizations that evolve their BI&A initiatives. From the literature review and interviews with field professionals, this work explore the main initiatives of organizations to obtain new data sources in BI&A information systems. The methodology approach used is multiple case study. The research used the Absorptive Capacity theory as analytical perspective, which offers elements to evaluate how organization obtains external information and use it into organizational context. There are discussed the main challenges to diversifying data sources, such as the complexity of new technologies, suppliers, data integration, among others. The results are presented exploring the constructs Acquisition, Assimilation, Transformation and Explotation, built in Absorptive Capacity theory, applied to the diversification of data sources. It was possible to notice that there are different external and/or not structured data usage levels in organization, as well as different organizational arrangements for consuming external data. The ways of consuming external data have effects on the investment allocation, data governance, organizational culture related to the use of data, and ultimately on the maturity of external and/or not structured data usage in a systematic way in the organization.

The exceeding supply over demand and very hard competitive conditions are nowadays the main features of the majority of sectors. A successful company is the one that is able to satisfy specific customers' needs, the one that has efficient cooperation with its suppliers throughout the whole supply chain and also the one that is able to speed up the in-house information exchange. Thus the company has to seek constantly new and innovative solutions. This is not possible without standardization and automatization of business processes. This master's thesis is dedicated to one of the possible solutions -- the Product Information Management (PIM). Since it is intended for business managers (without deep IT knowledge), at the beginning it answers the question why it is so important to know master data and to manage it. It specializes in managing product data, brings its comprehensive overview and identifies the advantages and drawbacks of the implementation as well as financial and organizational impacts. The consecutive chapter deals with simplified yet applicable approach to data management analysis (with emphasis on the PIM) and based on research, it mentions main mistakes of the implementation. In addition to the overview of main vendors of the PIM solution, it presents the latest trends in the PIM. Besides internal data synchronization, the thesis analyses several product standards -- the fundamental step towards external data synchronization, the key topic of the practical part. The whole thesis is conceived to provide an organization with a simple yet compact and therefore very effective tool for master product data insight and thus to help it to gain a competitive advantage.