Explain the purpose of data compression and describe the difference between lossy and lossless compression, including when each is appropriate.

What this dot point is asking

WJEC asks you to explain why digital files are often made smaller before being stored or sent, and to describe the two families of methods used to do it, lossy and lossless, including the trade-off each involves and when each is the sensible choice. This builds directly on the file-size work: compression is how those large image and sound files are made practical to share.

Why compress at all

Files, especially images, audio and video, can be very large. Compression tackles the practical problems this causes.

Without compression, a phone would hold far fewer photos and a web page full of images would load slowly, so compression is essential to everyday digital use.

Lossy compression

Lossy methods achieve large reductions by throwing some data away.

Because the saving is large, lossy compression is used where a small file matters more than perfect fidelity: photographs, streamed music, and video. Each time a lossy file is re-compressed, more quality can be lost.

Lossless compression

Lossless methods reduce size while keeping every bit of the original.

Lossless is essential where losing any data would be unacceptable: text documents, spreadsheets, databases and program files, where a single altered character or instruction could cause errors.

Choosing between them

The decision comes down to whether any loss of data can be tolerated.

How much compression saves

A common exam follow-up asks you to compare a file size before and after compression, or to state the saving. The method is to subtract the compressed size from the original, or to express the compressed size as a fraction of the original. For example, if a 10 MB photo is compressed to 2 MB, the saving is 8 MB, and the compressed file is one fifth (20 percent) of the original. Lossy compression typically gives large savings like this, while lossless gives more modest savings because it cannot discard any data. Being able to put a number on the saving, using the unit conversions from the rest of the Data topic, turns a description of compression into the quantified answer markers reward.

Streaming and progressive loading

Compression is what makes streaming possible: a video or music service compresses the media so it can be sent over the internet fast enough to play as it arrives, rather than waiting for the whole file to download. Lossy compression is used here because a small loss of quality is acceptable in return for a much smaller stream that keeps up with the connection. The same idea explains why an image on a slow connection may appear blurry first and then sharpen: a compressed, low-detail version loads quickly and is refined as more data arrives. Linking compression to these everyday experiences shows you understand why the technique matters, not just what it is.

Why this matters

Compression is the reason streaming, photo sharing and large downloads are practical. Understanding the trade-off lets you justify real choices, such as why a designer keeps an uncompressed master file but exports a compressed copy for the web, or why software is distributed in a lossless compressed form so it installs correctly. It ties together everything in the Data topic: representation creates the data, units measure it, and compression manages its size.