How is data wrangling different than a data cube processing? -


i know data cube transforming multi-dimensional data keeps changing time, whereas data wrangling definition says it's transforming data making more valuable.

isn't data cube more meaningful , valuable piece of denormalized data ? haven't been able find example clear symmetry, both sound same me.. please help!

i found this article claims bring perspective question -

i did not find true example after reading , speaking data analysts following line calls closure me -

data wrangling applied functional experts on data in question clean off of it's veracity

on other hand

data cube processing when data analyst projection on structured data output report kpis (key performance indicators)

one 'cleanup' whereas 'projection'


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