DaDaDa: A Dataset for Data Pricing in Data Marketplaces
Recognizing the value of data, data transactions are increasingly common, giving rise to many data marketplaces, e.g., AWS Marketplace, Databricks, and Datarade. However, determining the appropriate prices for data products remains a significant challenge due to the unique properties of data products. Traditional pricing methods in economics can be categorized into the cost approach, the income approach, and the sales comparison approach.
- ▪Recognizing the value of data, data transactions are increasingly common, giving rise to many data marketplaces, e.g., AWS Marketplace, Databricks, and Datarade.
- ▪However, determining the appropriate prices for data products remains a significant challenge due to the unique properties of data products.
- ▪Traditional pricing methods in economics can be categorized into the cost approach, the income approach, and the sales comparison approach.
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Computer Science > Machine Learning arXiv:2607.08785 (cs) [Submitted on 13 Jun 2026] Title:DaDaDa: A Dataset for Data Pricing in Data Marketplaces Authors:Qiheng Sun, Hongwei Zhang, Junxu Liu, Xiaokai Mao, Jinfei Liu, Kui Ren, Haibo Hu View a PDF of the paper titled DaDaDa: A Dataset for Data Pricing in Data Marketplaces, by Qiheng Sun and 6 other authors View PDF HTML (experimental) Abstract:High-quality data drives machine learning advances across industries. Recognizing the value of data, data transactions are increasingly common, giving rise to many data marketplaces, e.g., AWS Marketplace, Databricks, and Datarade. However, determining the appropriate prices for data products remains a significant challenge due to the unique properties of data products.
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