Friday, November 27, 2020

OBG: Missing Data -- "Horizontal Decomposition" Part 2




Note: To demonstrate the correctness and stability of a sound foundation relative to the industry's fad-driven "cookbook" practices, I am re-publishing "Oldies But Goodies" material from the old DBDebunk.com (2000-06), so that you can judge for yourself how well my arguments hold up and whether the industry has progressed beyond the misconceptions those arguments were intended to dispel. I may break long pieces into multiple posts, revise, and/or add comments and references.

In Part 1 we re-published a reader's response to "horizontal decomposition" -- Hugh Darwen's How to Handle Missing Information without Using NULLs  -- in comparison to our The Final NULL in the Coffin: A Relational Solution to Missing Data). Here's Hugh's response.

Sunday, November 22, 2020

OBG: Missing Data -- "Horizontal Decomposition" Part 1



Note: To demonstrate the correctness and stability of a sound foundation relative to the industry's fad-driven "cookbook" practices, I am re-publishing as "Oldies But Goodies" material from the old DBDebunk.com (2000-06), so that you can judge for yourself how well my arguments hold up and whether the industry has progressed beyond the misconceptions those arguments were intended to dispel. I may break long pieces into multiple posts, revise, and/or add comments and references.
 

“I'm excited to share a data.world research partnership with Prof Leonid Libkin and Paolo Guagliardo from The University of Edinburgh. Our goal is to understand how NULL values are used in the real word to bridge theory and practice. Please help us by participating in a survey.”


Thus a recent announcement on LinkedIn, which triggered reactions in praise of this "much needed effort".

Sigh! SQL's NULL is a blunder unworthy of research. The commonly used "NULL value" is a contradiction in terms, indicating that industry surveys are not a path to enlightening. The real issue is, of course, missing data, which is governed by long studied and well understood logic[1,2,3,4], though apparently not in the industry and today's academia.

In 2004 we published The Final NULL in the Coffin: A Relational Solution to Missing Data (a paper revised since) that we believe is theoretically sound and, importantly, consistent with McGoveran's work re-interpreting, extending and formalizing Codd's RDM[5]. At the time it generated a series of exchanges with readers, which were posted at the old DBDebunk (2000-2006). In light of the above they warrant re-production.

I start with the first, split in three parts: In this Part 1 a reader's reaction to both our solution and Hugh Darwen's "horizontal decomposition" alternative, How to Handle Missing Information without Using NULLs; Hugh's reply is in Part 2 and mine -- re-written to bring up to date with current state of knowledge and for clarity --
is in Part 3.

Note: In a later book Darwen dedicated a chapter to a "multi-relation" approach which seems an allusion to our solution.

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