Creating a Data Transformation Pipeline with Cloud Dataprep Reviews

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Harsh M. · Reviewed over 1 year ago

Glenn F. · Reviewed over 1 year ago

Aaron D. · Reviewed over 1 year ago

Tuhin R. · Reviewed over 1 year ago

Could not complete the lab because verification was not working.

Roel T. · Reviewed over 1 year ago

satisfied

Saran M. · Reviewed over 1 year ago

Gadi B. · Reviewed over 1 year ago

Kartik K. · Reviewed over 1 year ago

This was a really nice lab!

Oluwapelumi S. · Reviewed over 1 year 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 over 1 year ago

Alexis V. · Reviewed over 1 year ago

Fredrick J. · Reviewed over 1 year ago

Tanu G. · Reviewed over 1 year ago

Sudhanshu D. · Reviewed over 1 year ago

Marius H. · Reviewed over 1 year ago

Himanshu A. · Reviewed over 1 year ago

璟宏 劉. · Reviewed over 1 year ago

Eduardo C. · Reviewed over 1 year ago

yetendra K. · Reviewed over 1 year ago

EIKI T. · Reviewed over 1 year ago

Abdurrahman A. · Reviewed over 1 year ago

elkana m. · Reviewed over 1 year ago

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

Michael K. · Reviewed over 1 year ago

Juan Carlos B. · Reviewed over 1 year ago

Avadut K. · Reviewed over 1 year ago