IGCSE Computer Science 0478 — 1.3 Data Storage and Compression Hangman

The 45 key terms

1bit

A bit is a single binary digit that is either 0 or 1, like a switch that is off (0) or on (1). A group of 8 bits is called a byte.

2nibble

A nibble is a group of 4 bits, so half a byte. Two nibbles make 1 byte. One hexadecimal digit fits exactly in one nibble.

3KiB

A kibibyte (KiB) is a unit of data storage equal to 1024 bytes. The kibi prefix means 1024, and KiB is the first unit above the byte.

4mebibyte (MiB)

A unit of data storage equal to 1024 kibibytes (KiB). The mebi prefix means 1024 squared. A typical photo or song is a few MiB in size.

5gibibyte

A gibibyte (GiB) is a unit of data storage equal to 1024 mebibytes (MiB). A film or memory stick is often a few GiB. The gibi prefix means 1024 cubed bytes.

6TiB

Tebibyte: a unit of data storage equal to 1024 GiB. The tebi prefix means 1024 to the power 4. A typical hard drive might hold 1 or 2 TiB.

7PiB

A pebibyte (PiB) is a unit of data storage equal to 1024 tebibytes (TiB). It is used for very large amounts of data, such as in big data centres.

8EiB

Exbibyte: a unit of data storage equal to 1024 pebibytes (PiB). It is the largest unit in the IGCSE syllabus.

9bit, nibble, byte, KiB, MiB, GiB, TiB, PiB, EiB

The storage unit ladder from smallest to largest. Above the byte, each unit is 1024 times the one before: 1 KiB = 1024 bytes, 1 MiB = 1024 KiB, and so on up to EiB.

11bytes = bits / 8

Divide bits by 8 to get bytes. Multiply bytes by 8 to get bits. A nibble is 4 bits, so 2 nibbles make 1 byte. Example: 24 bits / 8 = 3 bytes, and 5 bytes x 8 = 40 bits.

12divide by 1024

To convert to the next larger unit (bytes to KiB, KiB to MiB, MiB to GiB), divide the size by 1024. The answer may not be a whole number.

13size * 1024

To convert to the next smaller unit (GiB to MiB, MiB to KiB, KiB to bytes), multiply by 1024. The answer should be a bigger number than the one you started with.

141024 per step

To convert across several units, divide by 1024 for each step up the ladder or multiply by 1024 for each step down. Bytes to MiB is two steps, so divide by 1024 twice.

15unit asked

Finish a storage calculation by converting the result into the unit the question asks for, then write that unit with your answer, for example 2 MiB.

16resolution

The number of pixels in an image, given as width x height (like 1920 x 1080). More pixels give more detail but make a bigger file.

17colour depth

The number of bits used to store the colour of each pixel. More bits per pixel means more possible colours, such as 1 bit for 2 colours or 24 bits for true colour.

18colours = 2^n

A colour depth of n bits gives 2^n different colours, so each extra bit doubles the number. For example, 2 bits give 4 colours and 8 bits give 256 colours.

19pixels = width * height

Total pixels = pixels per row times number of rows. For 1920 x 1080 that is 2,073,600 pixels. This is the first step when working out image file size.

20width x height x bits per pixel

The size of an uncompressed bitmap image in bits. Multiply width by height by the bits used for each pixel, then divide by 8 to get bytes.

21bytes / 1024 / 1024

After finding an image size in bytes, divide by 1024 once for KiB, twice for MiB and three times for GiB, to give the answer in the unit the question asks for.

22sample rate

The number of sound measurements taken each second, in hertz (Hz). CDs use 44,100 Hz. A higher rate gives better quality but makes a bigger file.

23sample resolution

The number of bits used to store each sample of a sound. More bits give more possible volume levels and a more accurate recording. 16 bits per sample is common.

241 kHz = 1000 Hz

Sample rate is measured in hertz (Hz), the number of samples per second. 1 kHz is 1000 Hz, so 44.1 kHz is 44100 Hz. Frequency uses 1000, not 1024.

25seconds = minutes x 60

Sound length must be in seconds before using it in a file size calculation, so multiply minutes by 60 (add any extra seconds). Length is then the third factor in the formula.

26size = sample rate x resolution x seconds

Uncompressed sound file size in bits is the sample rate (Hz) times the sample resolution (bits) times the length in seconds. Divide the bits by 8 to get bytes.

27bits / 8 / 1024

Divide the sound size in bits by 8 to get bytes, then by 1024 to get KiB. Divide by 1024 again to get MiB. Stop at the unit the question asks for.

28file size <= capacity

A file fits if its size is less than or equal to the free space. First convert both to the same unit, such as bytes or MiB, then compare the two numbers.

29Compression

Reducing file size by removing or simplifying data, sometimes losing quality.

30compression saves storage

Compressed files are smaller, so they take up less storage space. This means more photos or songs fit on a device, and less storage needs to be bought.

31compression saves bandwidth

A compressed file has fewer bits to send, so it uses less of the shared network bandwidth. This eases congestion and helps video and audio stream smoothly.

32transmission time

The time a file takes to upload, download or send. A smaller compressed file has a shorter transmission time, so downloads, email attachments and web pages are quicker.

33lossy compression

Shrinks a file by permanently throwing away detail people are unlikely to notice, so the original can't be rebuilt exactly. JPEG and MP3 use it.

34permanent loss

Data removed by lossy compression is gone for good, so the original quality cannot be restored. Keep the original file, as re-saving or compressing again only lowers quality further.

35higher resolution and colour depth

Raising either one improves image quality (sharper detail, smoother colours) but stores more bits, so the file size gets larger.

36higher sample rate or resolution

Raising the sample rate or sample resolution records the sound more accurately, but it also makes the audio file bigger. Lowering either does the opposite: less accurate, smaller file.

37lossy image compression

Reduces an image's resolution or colour depth to shrink the file. Detail is lost for good. Recalculate width x height x depth to see the saving.

38lossy sound compression

Lowering the sample rate or sample resolution of a sound so it needs fewer bits. The file gets smaller, but the lost sound detail can never be recovered.

39redundancy

Repeated or predictable data, like a run of the same letter or colour, that can be stored in a shorter form without losing any information.

40lossless compression

Shrinks a file so the exact original data can be rebuilt perfectly, with nothing lost. ZIP and PNG use it. Needed for text and programs.

423C2D = CCCDD

Decoding run-length data: read each count then its character, and write that character that many times. 3C means CCC and 2D means DD, so 3C2D expands back to CCCDD.

43RLE pixel row

Run-length encoding of a pixel row stores each run of same-coloured pixels as a count then a colour code, in order along the row. E.g. WWWBB becomes 3W2B.

44RLE decode

Repeat each colour code count times along the row to rebuild the pixels, e.g. 3R2B gives RRRBB. Then check the row adds up to the image width.

45RLE expansion

When data has few repeats, run-length encoding adds a count to every character, so the result can be longer than the original. It only saves space when the data has long runs.

46lossy vs lossless

Lossy makes smaller files but permanently removes data; lossless keeps all data so the original can be restored, but saves less space.

47Lossless vs lossy choice

Pick lossless (PNG, ZIP, FLAC) when every detail must be kept. Pick lossy (JPEG, MP3, MP4) when a smaller file matters more than perfect quality.