Month: September 2016

PCA in Spotfire TERR

PCA (Principal Component Analysis) is a core data science technique for not only understanding colinearity of independent variables in a dataset, but can provide a reduced dimensional model by rotating your high-D data into lower dimensions. Here’s some quick info on getting PCA in Spotfire. If you want more info on PCA, of course check out Wikipedia or a great interactive example on Setosa.

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You’ll conquer the present suspiciously fast if you smell of the future….and stink of the past.

Administrating Spotfire — currency data types

  • Do you wonder why some columns from SQL come across as currency data types and why others come across as real data types?
  • Are you tired of manually changing currency data types to real data types?
  • Are you tired of using transformations to change currency data types to real data types?

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Guest Spotfire blogger residing in Whitefish, MT.  Working for SM Energy’s Advanced Analytics and Emerging Technology team!