Investigation of Data Extraction Process with Anonymizations Using Different Data Types

This research investigates the process of data extraction with anonymization using various data types. The methodology includes analyzing anonymization algorithms and employing artificial intelligence for data collection. The study reveals that integrating multiple anonymization techniques enhances both security and accuracy in data analysis. Main results demonstrate improvements in anonymized data handling efficiency and reduced risk of personal data exposure.