Description: Narrow data refers to datasets that have been limited in scope to enhance privacy and reduce the risk of identification. This process involves the removal or modification of sensitive information that could be linked to specific individuals, allowing for data analysis without compromising the confidentiality of individuals. Data reduction can include techniques such as aggregation, where data from multiple sources is combined to present general information rather than specific details, or the suppression of certain attributes that could be used to identify an individual. This practice is particularly relevant in the context of growing concerns about privacy in the digital age, where the collection and analysis of large volumes of data are common. By implementing narrow data, organizations can comply with data protection regulations, such as GDPR in Europe, while still gaining valuable insights without risking users’ personal information. In summary, narrow data is an essential tool for balancing the need for data analysis with the protection of individual privacy.
