Editing 2739: Data Quality

{{comic
| number    = 2739
| date      = February 17, 2023
| title     = Data Quality
| image     = data_quality_2x.png
| imagesize = 671x211px
| noexpand  = true
| titletext = [exclamation about how cute your cat is] -> [last 4 digits of your cat's chip ID] -> [your cat's full chip ID] -> [a drawing of your cat] -> [photo of your cat] -> [clone of your cat] -> [your actual cat] -> [my better cat]
}}

==Explanation==
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Digital data are transferred in bits, and {{w|data loss}} is the process by which some of these bits are lost or altered during data transport. Data can also be compressed to make transmission and/or storage more efficient; some {{w|compression algorithms}} discard some data to improve the compression (this can be acceptable in audio or visual data, since the difference may be hard for humans to perceive).

This comic shows a chart in the form of a line, moving in increasing quality from most lossy to most lossless. However, the highest quality, "better data", is using a different sense of the term "quality". In the context of data transmission or compression, it refers to how accurately the result represents the original. But in this case, he's referring to its more general excellence.

The title text uses your cat as an example of this range of losses (or, in the case of the latter reaches of the graph, gains) in the data. The most lossy is an exclamation about how cute your cat is, which is ephemeral and obviously carries very little significance in terms of actually providing specific, transferrable information about your cat. The example then progresses into your cat's chip ID; presumably your cat has been microchipped, and between the last four digits (commonly used in sensitive information as an identifier without revealing the full number) or the entire chip ID, provides a still-uninformative yet slightly improved way of identifying your cat. A drawing of your cat and a photo of your cat would portray the cat reasonably well, while a clone of your cat and (of course) your actual cat would be the best way of gaining data about your cat. However, as in the actual comic, the final, most lossless (in this case, with the most gain) form of data transfer has nothing to do with your cat, but is simply Randall's better cat. This is apparently made out by Randall to be the pinnacle of cat data.

=== Details ===
{| class="wikitable" 
|-
! Item
! Explanation
|-
| {{w|Bloom filter}}
| A Bloom filter is a probabilistic data structure that can efficiently say whether an element is ''probably'' part of the dataset, while it can say "element is not in set" with 100% accuracy. If a Bloom filter is used to compress the contents of a book, the Bloom filter can re-tell a similar story - just by guessing.
|-
| {{w|Hash table}}
| A hash table allows you to find data very fast. Randall probably means hashing the contents of entire books. Calculating a hash value for an entire book means that there is (most probably) a unique relationship between the book and a hash value - e.g. "58b8893b2a116d4966f31236eb2c77c4172d00e9". This means the book will yield this exact hash value, though it's impossible to reconstruct the book's content from a hash vaue. It is a highly efficient, but is meaningless: An average book contains several millions of bits, yet the SHA-2 hash has only 256 bits.
|-
| {{w|JPEG|JPG}}, {{w|GIF}}, {{w|MPEG-1|MPEG}}
| Image and video formats that are considered 'lossy'. JPG (or "JPEG") format and the MPEG {{w|MPEG-2|group}} {{w|Advanced Video Coding|of}} formats typically use a range of data-compression methods that save space by selectively fudging (thus losing) what details it can of the image (and audio, where appropriate), to make disproportionate gains in compression; best used for real world images (and films) where real-world 'noise' can afford to be replaced by a more compressible vesion, without too much obvious change.
GIF compression is not 'lossy' in the same way, i.e. whatever it is asked to encode can be faithfully decoded, but Randall may consider its limitations (it can only write images of 256 unique hues, albeit that these can come from anywhere across the whole 65,536 "True color" range, plus transparency) to be a form of loss, as conversion from a more sophisticated format (e.g. PNG, below) could lose many of the subtle shades of the original and produce an inferior image. For this reason, GIF format became one best left to render diagrams and other computer-generated imagery with swathes of identical pixels and mostly sharp edges (and to utilise the optional transparent mask). Alternatively, he may just have included it as a joke/nerd-snipe.
|-
| {{w|PNG}}, {{w|ZIP (file format)|ZIP}}, {{w|TIFF}}, {{w|WAV}}
| A series of formats using lossless compression. PNG and TIFF are image formats, that are suitable for photos but without resorting to reduced accuracy in order to assist compression. WAV is an audio format that also does not arbitrarily sacrifice 'unnecessary' details, unlike the more recently developed {{w|MP3|MPEG Audio Layer III}} which has become the defacto consumer audio format for many.
ZIP is a generic compression algorithm(/format) that can be used to store any other digital file, for exact decompression later on, although any file(s) already compressed in some way are not likely to compress significantly more.
|-
| Parity bits for error detection
| In the number 135, the sum of digits is 9. So, the number 135 could be written as "135-9". If the number was tampered with, the parity bits could tell you so (in some cases), or possibly that the parity itself was the digit that was miswritten. But a change from "135" to "153" could not be detected that way. There are more reliable means to detect errors: The obsolete CRC-32 and MD5, and the much more modern {{w|Secure Hash Algorithm|SHA}}.
|-
| Parity bits for error correction
| There are ways to restore the original data with the given additional data. One method is to 'overload' with multiple different methods of error-detection parity such that any small enough corruption of data (including of the parity bits themselves) can be reconstructed to the correct original value. One of the first such methods is {{w|Hamming(7,4)}}, invented around 1950.
|}

==Transcript==
:[A line chart is shown with eight unevenly-spaced ticks each one with a label beneath the line. Above the middle of the line there is a dotted vertical line with a word on either side of this divider. Above the chart there is a big caption with an arrow pointing right beneath it.]
:<big>Data Quality</big>
:Lossy ┊ Lossless

:[Labels to the left of the dotted line from left to right:]
:Someone who once saw the data describing it at a party
:Bloom filter
:Hash table
:JPEG, GIF MPEG

:[Labels to the right of the dotted line from left to right:]
:PNG, ZIP, TIFF, WAV, Raw data
:Raw data + parity bits for error detection
:Raw data + parity bits for error ''correction''
:Better data

{{comic discussion}}

[[Category:Charts]]
[[Category:Cats]]