Data preparation has an important role in data analysis, and it is time and resource-consuming, both in terms of human and computational resources. The "Discount quality for responsible data science" project aims to focus on data-quality-based data preparation, analyzing the main characteristics of related tasks, and proposing methods for improving the sustainability of the data preparation tasks, considering also new emerging techniques based on generative AI. The paper discusses the main challenges that emerged in the initial research work in the project, as well as possible strategies for developing more sustainable data preparation frameworks.
Pernici, B., Cappiello, C., Ramalli, E., Palmonari, M., Belotti, F., De Paoli, F., et al. (2024). The Future of Sustainable Data Preparation. In Proceedings of the 32nd Symposium on Advanced Database Systems (pp.486-497). CEUR-WS.
The Future of Sustainable Data Preparation
Palmonari M.;Belotti F.;De Paoli F.;
2024
Abstract
Data preparation has an important role in data analysis, and it is time and resource-consuming, both in terms of human and computational resources. The "Discount quality for responsible data science" project aims to focus on data-quality-based data preparation, analyzing the main characteristics of related tasks, and proposing methods for improving the sustainability of the data preparation tasks, considering also new emerging techniques based on generative AI. The paper discusses the main challenges that emerged in the initial research work in the project, as well as possible strategies for developing more sustainable data preparation frameworks.
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