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

Kuan C. · Revisado há almost 2 years

Felipe M. · Revisado há almost 2 years

Kuan C. · Revisado há almost 2 years

Vedansh C. · Revisado há almost 2 years

Sebastian L. · Revisado há almost 2 years

Miguel M. · Revisado há almost 2 years

Not working

Harsh M. · Revisado há almost 2 years

Glenn F. · Revisado há almost 2 years

Aaron D. · Revisado há almost 2 years

Tuhin R. · Revisado há almost 2 years

Could not complete the lab because verification was not working.

Roel T. · Revisado há almost 2 years

satisfied

Saran M. · Revisado há almost 2 years

Gadi B. · Revisado há almost 2 years

Kartik K. · Revisado há almost 2 years

This was a really nice lab!

Oluwapelumi S. · Revisado há almost 2 years

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 almost 2 years

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yetendra K. · Revisado há almost 2 years