Databricks Certified Data Engineer - Professional

Explanation

Hashing is the correct answer because it can obscure personal information by outputting a string of randomized characters. Here's why:

• Hashing: Converts input data into a fixed-length string of characters using a mathematical algorithm. The output (hash) appears random and cannot be reversed to reveal the original data, making it ideal for obscuring personal information while maintaining data integrity.

Let's examine why the other options are incorrect:

• A. Tokenization: Replaces sensitive data with non-sensitive tokens, but these tokens are typically structured and reversible (with access to the tokenization system), not randomized character strings.

• B. Categorical generalization: Groups data into broader categories (e.g., age ranges, income brackets), which reduces precision but doesn't produce randomized character strings.

• C. Binning: Divides continuous data into discrete intervals or "bins" (e.g., grouping ages into 0-20, 21-40, etc.), which is a form of data reduction but doesn't create randomized character outputs.

Hashing is commonly used in data security and privacy applications to protect sensitive information while still allowing for data processing and analysis.