From the course: Introduction to Modern Data Engineering with Snowflake
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Data transformations with snowpark - Snowflake Tutorial
From the course: Introduction to Modern Data Engineering with Snowflake
Data transformations with snowpark
If you're like me, then SQL might not be your preferred language of choice. I personally prefer Python, and I love that with Snowpark, I can use Python to perform my data transformations. With Snowpark, you can perform data transformations in Python, Java, or Scala. Snowpark allows you to configure the runtimes for these languages, meaning you can perform data transformations with, say, Python 3.9 or 3.10 or whichever version fits your language and use case best. Snowpark provides a DataFrame API for processing your data and performing your data transformations. The general pattern is that you'll create DataFrames using your data, perform whatever sorts of transformations you need to perform, and usually write those results back to new views or tables. If you've used PySpark prior to this or any other data framework with a DataFrame API, your Snowpark experience will feel very similar. Finally, if you've ever attempted to perform large-scale data operations using your own computer's…
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What are data transformations?2m 19s
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Data transformations with SQL5m 38s
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Data transformations with snowpark7m 7s
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Computations with user-defined functions7m 15s
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Efficient transformations with streams8m 9s
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Complex procedural logic with stored procedures6m 31s
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Automatic transformations with dynamic tables8m 7s
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Data transformations in visual studio code (optional)4m 34s
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Recap and best practices for data transformations1m 39s
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