Creating a Data Transformation Pipeline with Cloud Dataprep Reviews

This was a really nice lab!

Oluwapelumi S. · Reviewed about 1 month ago

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. · Reviewed about 1 month ago

Alexis V. · Reviewed about 1 month ago

Fredrick J. · Reviewed about 1 month ago

Tanu G. · Reviewed about 1 month ago

Sudhanshu D. · Reviewed about 1 month ago

Marius H. · Reviewed about 1 month ago

Himanshu A. · Reviewed about 1 month ago

璟宏 劉. · Reviewed about 1 month ago

Eduardo C. · Reviewed about 1 month ago

yetendra K. · Reviewed about 1 month ago

栄紀 竹. · Reviewed about 1 month ago

Abdurrahman A. · Reviewed about 1 month ago

elkana m. · Reviewed about 1 month ago

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

Michael K. · Reviewed about 1 month ago

Juan Carlos B. · Reviewed about 1 month ago

Avadut K. · Reviewed about 1 month ago

Pankaj G. · Reviewed about 1 month ago

Prasad I. · Reviewed about 1 month ago

sara p. · Reviewed about 1 month ago

Priyadeep M. · Reviewed about 1 month ago

ARRAMSHETTY S. · Reviewed about 1 month ago

sara p. · Reviewed about 1 month ago

Amritansh S. · Reviewed about 1 month ago

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. · Reviewed about 1 month ago