Which term describes shrinking without losing data?

Which term describes shrinking without losing data?

• A. Lossy compression
• B. Data compression
• C. Lossless compression
• D. Sample resolution

Answer: (C)

Shrinking data without losing any information is about lossless compression. It means you can compress the data and then decompress it to get back exactly the original, bit for bit. This is ideal when every detail matters, like text, program code, or data files. If some information is discarded to make the file smaller, that’s lossy compression, which trades accuracy for a smaller size. More general terms like data compression describe reducing size in general but don’t specify whether data is preserved. Sample resolution isn’t about compression at all; it refers to how finely a signal is measured or represented, which affects quality rather than whether the original data can be perfectly reconstructed.

Shrinking data without losing any information is about lossless compression. It means you can compress the data and then decompress it to get back exactly the original, bit for bit. This is ideal when every detail matters, like text, program code, or data files. If some information is discarded to make the file smaller, that’s lossy compression, which trades accuracy for a smaller size. More general terms like data compression describe reducing size in general but don’t specify whether data is preserved. Sample resolution isn’t about compression at all; it refers to how finely a signal is measured or represented, which affects quality rather than whether the original data can be perfectly reconstructed.