Data generalization is an old data anonymization method. To protect individuals' data in a dataset, unique values are replaced with generic values, which results in a privacy-utility trade off. K-anonymity is one of the most frequently applied generalization techniques. Unfortunately, generalization fails to protect privacy and also greatly reduces the utility of the data. Read more about the disadvantages of generalization. https://mostly.ai/blog/3-reasons-to-drop-classic-anonymization-and-upgrade-to-synthetic-data/