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

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 2 years

Alexis V. · Revisado há about 2 years

Fredrick J. · Revisado há about 2 years

Tanu G. · Revisado há about 2 years

Sudhanshu D. · Revisado há about 2 years

Marius H. · Revisado há about 2 years

Himanshu A. · Revisado há about 2 years

璟宏 劉. · Revisado há about 2 years

Eduardo C. · Revisado há about 2 years

yetendra K. · Revisado há about 2 years

EIKI T. · Revisado há about 2 years

Abdurrahman A. · Revisado há about 2 years

elkana m. · Revisado há about 2 years

last part for output in dataprep was hard to understand (esp. the workflow/labeling does not fit to the lab

Michael K. · Revisado há about 2 years

Juan Carlos B. · Revisado há about 2 years

Avadut K. · Revisado há about 2 years

Pankaj G. · Revisado há about 2 years

Prasad I. · Revisado há about 2 years

sara p. · Revisado há about 2 years

Priyadeep M. · Revisado há about 2 years

ARRAMSHETTY S. · Revisado há about 2 years

sara p. · Revisado há about 2 years

Amritansh S. · Revisado há about 2 years

Did everything as proposed, was not able to validate last step several time. Would be nice to have hints why it did not work...

adrien p. · Revisado há about 2 years

Vrajkumar P. · Revisado há about 2 years