Dedico este trabalho às pessoas que são a razão de minha vida: meus pais Segismundo e Lídia, minha mulher Elisabete e meus filhos André, Elisa e Paulo, pelo amor e incentivo que sempre me deram. v AGRADECIMENTOS Ao Prof. Dr. Martinho Isnard Ribeiro de Almeida, mais que professor e orientador, amigo e incentivador. Aos membros da banca do exame de qualificação, Profs. Drs. Leonel Cezar Rodrigues e Maurício Fernandes Pereira, pelos ensinamentos. Aos profs. Leo Ferreira Arantes, Messias Mercadante de Castro e Sérgio Roberto Porto de Almeida, por me levarem à vida acadêmica. Aos Profs. Drs. Emerson Antonio Maccari e Walter Furlan, pelo despreendimento e apoio. Aos demais membros do Grupo de Pesquisa Planejamento Estratégico e Empreendedorismo da FEA-USP,

No abstract

Forma de avaliação: double blind review Esta revista é (e sempre foi) eletrônica para ajudar a proteger o meio ambiente. Agora ela volta a ser diagramada em uma única coluna, para facilitar a leitura na tela do computador. Mas, caso deseje imprimir esse artigo, saiba que ele foi editorado com uma fonte mais ecológica, a Eco Sans, que gasta menos tinta.

Purpose: To present the planning for the digital transformation of Brazilian higher education institutions (HEI) and to measure their degree of digital mastery, according to Westerman, Calméjane, Bonnet, Ferraris, and McAfee (2011). Originality/value: Some studies evaluate digital transformation and/or the degree of digital mastery carried out in HEI individually. However, those that assess them comparatively have not been identified, allowing to draw a baseline to assist managers in benchmarking processes. Design/methodology/approach: It is an exploratory, qualitative research, with field study, in which the secondary data were obtained through bibliographic and documentary sources and the primary data through semi-structured interviews. For this purpose, representatives of ten private HEI were interviewed using an instrument consisting of a script of questions. The content was analyzed according to the model of Bardin (2011) and supported by the tool Iramuteq. The findings served as an input for completing the digital mastery questionnaires. Findings: Elements identified in the research refer to the fact that the evaluated HEI have good maturity in their digital transformation processes. Such allegations could be verified from the evaluation of digital mastery, which found that most institutions have a good level of digitalization and that, despite having some limitations related to the development of digital and leadership skills, can be considered digital masters.

Data Science (DS) is an interdisciplinary research area that uses concepts based on Big Data Analytics, Programming Languages and Mathematical fundamentals to develop research into insight discovery from datasets. The data-driven decision-making approach has become a challenge for researchers and lecturers in the Information Systems area. This is because the skills and theoretical issues require a heavy course workload and high number of class hours. This work introduces a discussion of the insertion of the DS subject in Information Systems courses, and researchers' efforts to establish goals for professionals and lecturers involved in DS. IntroductionThe proliferation of computational systems in the industry has caused significant changes in the way data are collected, transmitted and analyzed [Turban et al. 2010]. In addition, there is considerable progress in the management of persistent systems and Data Base Management System (DBMS). The advance started with Peter Chen [Chen 1976] who proposed the E-R diagram to aid the design of databases and defined the requirements of problems, entities, attributes and relationships in a graphical way. Complementarily, DBMS has been consolidated as the main database approach, ensuring the properties such as Atomicity, Consistency, Isolation and Durability, called ACID [Silberschatz et al. 2006].Relational DBMS was the major resource to store data, facts or transactions, and it became a valuable tool for data analysis using tables, reports, maps or graphs, allowing approaches to manage or to monitor business in most areas of knowledge.Data generation has been growing exponentially and, which demands collecting, organizing, analyzing and extracting insights from data warehouses systematically, in heterogeneous environments, geographically distributed and, in distinct contexts of applications.