Como criar um pipeline de transformação de dados com o Cloud Dataprep avaliações

Detlev M. · Revisado há about 1 year

翔一 佐. · Revisado há about 1 year

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Srinivasa G. · Revisado há about 1 year

翔一 佐. · Revisado há about 1 year

Eduardo C. · Revisado há about 1 year

An H. · Revisado há about 1 year

Kuan C. · Revisado há about 1 year

Felipe M. · Revisado há about 1 year

Kuan C. · Revisado há about 1 year

Vedansh C. · Revisado há about 1 year

Sebastian L. · Revisado há about 1 year

Miguel M. · Revisado há about 1 year

Not working

Harsh M. · Revisado há about 1 year

Glenn F. · Revisado há about 1 year

Aaron D. · Revisado há about 1 year

Tuhin R. · Revisado há about 1 year

Could not complete the lab because verification was not working.

Roel T. · Revisado há about 1 year

satisfied

Saran M. · Revisado há about 1 year

Gadi B. · Revisado há about 1 year

Kartik K. · Revisado há about 1 year

This was a really nice lab!

Oluwapelumi S. · Revisado há about 1 year

I didn't like the naming of the columns as both camelCase and snake_case was used. Cleaning up the column names should be part of a data cleaning pipeline. Also hard coding the categorical values using a CASE statement is not best practice. Better to create a mapping table and join data.

Malte B. · Revisado há about 1 year

Alexis V. · Revisado há about 1 year

Fredrick J. · Revisado há about 1 year