surplus data problem
[ˈsɜr.pləs ˈdeɪ.tə ˈprɑb.ləm]
nounpl: surplus data problems
problema de dados excedentes
1. A challenge in data management where excessive or redundant data exceeds analytical capacity, storage resources, or processing capability, often resulting in inefficiency, increased costs, or difficulty in extracting meaningful insights
The company faced a surplus data problem after implementing multiple tracking systems that collected overlapping information.
A empresa enfrentou um problema de dados excedentes após implementar múltiplos sistemas de rastreamento que coletavam informações sobrepostas.
2. In machine learning and statistics, the issue of having more data than necessary to train a model effectively, which can lead to overfitting or computational inefficiency
The research team had to address the surplus data problem by implementing data sampling techniques.
A equipe de pesquisa teve que resolver o problema de dados excedentes implementando técnicas de amostragem de dados.
This is primarily a technical term used in data science, IT, and business analytics contexts in both Brazil and the United States. In Brazil, the phrase is increasingly common in tech startups and multinational corporations in São Paulo and Rio de Janeiro. In the USA, it reflects growing concerns about data management in the era of big data and artificial intelligence. The problem has become more culturally relevant as organizations struggle with digital transformation and data-driven decision-making.
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