Creating a Data Transformation Pipeline with Cloud Dataprep Reviews

翔一 佐. · Reviewed over 1 year ago

Zari B. · Reviewed over 1 year ago

Srinivasa G. · Reviewed over 1 year ago

翔一 佐. · Reviewed over 1 year ago

Eduardo C. · Reviewed over 1 year ago

An H. · Reviewed over 1 year ago

Kuan C. · Reviewed over 1 year ago

Felipe M. · Reviewed over 1 year ago

Kuan C. · Reviewed over 1 year ago

Vedansh C. · Reviewed over 1 year ago

Sebastian L. · Reviewed over 1 year ago

Miguel M. · Reviewed over 1 year ago

Not working

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