Data compression: Explain what data compression is.

The idea

Data compression is the process of reducing the number of bits needed to store or transmit a file, so the same information takes up less space. A compression method looks for redundancy — repeated or predictable patterns — and records it more economically. For example, a bitmap with large areas of identical colour can be stored by recording the colour once with a count of how many pixels share it, rather than storing every pixel separately. The compressed version must still allow the original data to be recovered, either exactly (lossless) or approximately (lossy).

What earns the marks

• Compression reduces the number of bits required to store or transmit data, so file size falls.
• Compression works by identifying and encoding redundancy such as repeated patterns or predictable values.
• The compressed data can be decompressed to recover the original information, exactly or approximately.
• Compression is not the same as deleting data or discarding information the user still needs.
• A correct MCQ choice describes encoding data more efficiently so fewer bits represent the same content.

Common mistakes and how to put them right

• Thinking compression means deleting parts of a file permanently.

  Put it right: Compression re-encodes the same information using fewer bits, and lossless methods recover it exactly.

• Confusing compression with changing file format.

  Put it right: Converting a file type does not necessarily reduce the bits stored, whereas compression specifically reduces the number of bits.

• Assuming compression always loses quality.

  Put it right: Lossless compression preserves the original data exactly, while only lossy compression discards some detail.

Exam tips

• Read every option and ask which one describes reducing the bits needed to represent the data.
• Eliminate options that describe deleting data or increasing file size.
• Link your chosen answer to the idea of redundancy being encoded more efficiently.