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Advanced Data Transformations in SnowPark | Snowflake Tutorial
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In this YouTube video, Aimpoint Digital’s Snowflake Solutions Architect, Christopher Marland, explains how we can move from ad-hoc data transformations to more professional, scalable, and automated transformations.
The video covers topics such as permanent UDFs, MERGEs, reading data from internal stages, and automating Snowpark for Python data transformations using stored procedures and tasks.
Prior knowledge of Snowpark for Python is recommended, but previous videos are available for reference.
This video provides a link to a Zip file containing the necessary code and demonstrates the data transformations using a Jupyter notebook.
Watch the video to learn more about enhancing your data transformations in Snowpark for Python.
00:00 Introduction
00:54 Earlier Video Links
01:15 What will be covered
02:01 Permanent UDFs
09:12 MERGE
10:20 MERGE Demo
13:56 Reading from Stages
16:14 Automation
17:45 Automation Demo
34:26 Conclusion
#python #snowflake #snowpark
The video covers topics such as permanent UDFs, MERGEs, reading data from internal stages, and automating Snowpark for Python data transformations using stored procedures and tasks.
Prior knowledge of Snowpark for Python is recommended, but previous videos are available for reference.
This video provides a link to a Zip file containing the necessary code and demonstrates the data transformations using a Jupyter notebook.
Watch the video to learn more about enhancing your data transformations in Snowpark for Python.
00:00 Introduction
00:54 Earlier Video Links
01:15 What will be covered
02:01 Permanent UDFs
09:12 MERGE
10:20 MERGE Demo
13:56 Reading from Stages
16:14 Automation
17:45 Automation Demo
34:26 Conclusion
#python #snowflake #snowpark
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