What is a main benefit of data aggregation?

Data aggregation is a privacy-enhancing technique that involves combining data from multiple individuals into summary statistics. This process inherently obscures individual-level information, making it difficult or impossible to link the summarized data back to a specific person. By presenting data in a grouped format (e.g., averages, counts), it serves as a method of de-identification, enhancing unlinkability and protecting individual privacy while still allowing for statistical analysis on the group.

A. Aggregation is a statistical process; meaningful analysis of the results, especially complex ones, still requires statistical expertise to avoid erroneous conclusions.
B. This describes defense-in-depth or layered security, a concept related to securing data systems, not the process of data aggregation itself.
C. Aggregation is typically more effective and less risky with larger data samples; drawing conclusions from small, aggregated samples can be statistically invalid.

1. National Institute of Standards and Technology (NIST). (2015). NISTIR 8053: De-Identification of Personal Information. p. 11, Section 2.2.2. The document describes generalization techniques, including aggregation, as methods to modify data to be less precise by "aggregating data across a group of individuals" to achieve de-identification.

2. El Emam, K., & Dankar, F. K. (2008). Protecting privacy using k-anonymity. Journal of the American Medical Informatics Association, 15(5), 627–637. https://doi.org/10.1197/jamia.M2706. This paper discusses aggregation as a form of generalization, a key technique for de-identification (p. 629).