Data management practices aligned with LGPD in the data science context


  • Elder Elisandro Schemberger



data science, innovation, LGPD, technology, interdisciplinary


Data management is a comprehensive process that includes data collection, storage, organization, and maintenance for efficient data analysis and use. With data generation at unprecedented volumes and at breakneck speed, effective data management has become an operational necessity and a competitive advantage. In the context of Data Science, data is the raw material for insights and innovations, making its proper management fundamental to ensure reliability and accuracy. This article stresses the importance of data governance, security and privacy, especially in view of the increase in data protection regulations such as the LGPD. It also addresses efficiency in data management as essential to driving innovation and facilitating data-driven decision-making in organizations and academia. The ability to manage large volumes of data is unique because well-managed data provides a valuable source of information, enabling trend identification, process optimization and strategic decision making, leading to innovation and competitive advantages. Also, this article discusses LGPD compliance, not only as a legal issue, but also as an opportunity for companies to build trust with their users by demonstrating a commitment to data security and privacy. Efficient data management also involves choosing appropriate tools and technologies and implementing policies that ensure data compliance and security.


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How to Cite

Schemberger, E. E. (2024). Data management practices aligned with LGPD in the data science context. OBSERVATÓRIO DE LA ECONOMÍA LATINOAMERICANA, 22(2), e3108.