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Culture War Roundup for the week of December 16, 2024

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Maybe I am bad at giving it context.

You, me, and everyone else. Sarah Constantin has a good post The Great Data Integration Schlep about the difficulty of getting all the relevant data together in a usable format in the context of manufacturing, but the issue is everywhere, not just manufacturing.

Obtaining the data is a hard human problem.

That is, people don’t want to give it to you.

[...]

Data cleaning doesn’t seem intellectually challenging, but it is surprisingly difficult to automate [...] Part of the issue is that the “reasonable” thing to do can depend on the “real-world” meaning of the data, which you need to consult a human expert on. For instance, are these two columns identical because they are literal duplicates of the same sensor output (and hence one can safely be deleted), or do they refer to two different sensors which happened to give the same readings in this run because the setting that would allow them to differ was switched off this time? The answer can’t be derived from the dataset, because the question pertains to the physical machine the data refers to; the ambiguity is inherently impossible to automate away using software alone.

There's a reason data scientists are paid the big bucks, and it sure isn't the difficulty of typing import pandas as pd.