Submitted by JOSIANE SANTOS DE OLIVEIRA (josianeso) on 2018-09-25T15:42:43Z No. of bitstreams: 1 Dirceu Silva Mello Corrêa Junior_.pdf: 5130564 bytes, checksum: 9921c0e8eafdc5eb26cc6cf6211bdb01 (MD5) / Made available in DSpace on 2018-09-25T15:42:43Z (GMT). No. of bitstreams: 1 Dirceu Silva Mello Corrêa Junior_.pdf: 5130564 bytes, checksum: 9921c0e8eafdc5eb26cc6cf6211bdb01 (MD5) Previous issue date: 2018-04-25 / Nenhuma / O Big Data é uma realidade social, com crescente impacto nos negócios. Entretanto, uma pesquisa realizada com executivos americanos de grandes corporações identificou uma baixa capacidade no aproveitamento efetivo dessa oportunidade de inteligência competitiva em suas empresas. Ao aprofundar o entendimento desse contexto, a partir da perspectiva de Orientação para o Mercado, a presente dissertação apresentou uma análise exploratória sobre a atual capacidade de grandes empresas com atuação nacional em absorver valor do Big Data, focando sua atenção num tipo específico de conteúdo, chamado Dado Não-Estruturado. Como resultado, identificou-se que as empresas estudadas se encontram em um momento peculiar para a gestão moderna de Orientação para o Mercado, uma espécie de processo evolutivo e de transição na compreensão e aproveitamento desse dilúvio de dados. Tal momento de adaptação é ainda reforçado por uma tendência para o uso de dados mais espontâneos dos consumidores. Neste estudo inicialmente são apresentadas cinco dimensões desse momento peculiar, abordando sistematicamente quesitos relacionados à organização interna; fornecedores e perfis de investimentos; adaptações internas; entre outros achados estratégicos. Após, também é detalhada a atual caminhada na efetiva compreensão do Big Data, a partir das práticas possíveis identificadas nesse contexto empresarial. / Big Data is a social reality with growing business impact. However, a survey of US executives of large corporations identified a low capacity to effectively exploit this competitive intelligence opportunity in their companies. In order to deepen the understanding of this context, from the perspective of Market Orientation, the present dissertation presented an exploratory analysis about the current capacity of large companies with national performance in absorbing Big Data value, focusing their attention on a type of content, called Unstructured Data. As a result, it was identified that the companies studied are in a peculiar moment for the modern management of Market Orientation, a sort of evolutionary process and of transition in the understanding and use of this deluge of data. This moment of adaptation is further reinforced by a trend towards the use of more spontaneous data from consumers. In this study, five dimensions of this peculiar moment are presented, systematically addressing questions related to internal organization; suppliers and investment profiles; internal adaptations; among other strategic findings. Afterwards, the current path to the understanding of Big Data is also detailed, based on the possible practices identified in this business context.

This study applies the knowledge, skills, and abilities (KSA) framework for eScience professionals to data service positions in academic libraries. Understanding the KSAs needed to provide data services is of crucial concern. The current study looks at KSAs of data professionals working in the United States academic libraries. An exploratory sequential mixed method design was adopted to discover the KSAs. The study was divided into two phases, a qualitative content analysis of 260 job advertisements for data professionals for Phase 1, and distribution of a self-administered online survey to data professionals working in academic libraries research data services (RDS) for Phase 2. The discovery of the KSAs from the content analysis of 260 job ads and the survey results from 167 data professionals were analyzed separately, and then Spearman rank order correlation was conducted in order to triangulate the data and compare results. The results from the study provide evidence on what hiring managers seek through job advertisements in terms of KSAs and which KSAs data professionals find to be important for working in RDS. The Spearman rank order correlation found strong agreement between job advertisement KSAs and data professionals perceptions of the KSAs.