Análise dos desafios e limitações do gerenciamento do Big Data: um recorte das indústrias automotivas situadas no Sul Fluminense

Abstract

In a context of digital transformation driven by Industry 4.0, Big Data has emerged as a strategic resource for the competitiveness of the automotive sector. However, its effective implementation faces significant obstacles, especially in specific industrial hubs. This study aims to identify and analyze the barriers and limitations to the progress of Big Data management in the automotive industries of South Fluminense, seeking to map the technological, human, and organizational challenges involved. The research, of an applied nature and using a mixed-methods approach, adopted the Design Science Research (DSR) methodology, which guided the creation and evaluation of an artifact, an Affinity Diagram, to synthesize and structure the identified problems. The methodological path included a systematic literature review and a survey with 62 professionals from the region. The main results reveal that although all companies use Big Data in a structured or limited way, obstacles persist. The most significant is cultural resistance to change (61.7%), followed by infrastructure limitations, such as a lack of hardware (48.3%), concerns about data security and privacy (46.7%), and a shortage of qualified professionals (43.3%). Despite these barriers, there is an positive perception of the value of Big Data, with 96.7% of respondents rating its impact as high or very high, primarily for improving strategic decision-making (93.3%) and reducing operational costs (78.3%). In this context, it is concluded that the effective adoption of Big Data is considered essential for the future competitiveness of the sector in South Fluminense; however, it depends on the coordinated overcoming of the identified challenges through investments in technology, professional training, and a data-driven cultural transformation. Thus, the research contributes to professional and academic circles by mapping and systematizing the main challenges of Big Data management in the automotive hub of Southern Fluminense, offering a regionalized diagnosis for managers and validating the theoretical challenges in a specific industrial context.