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ELT in Action

Feeling pretty good about running ETL processes? Well, it's time to give ELT pipelines a try. Like before, the extract(), load(), and transform() functions have been defined for you; all you'll have to worry about is running these functions. Good luck!

Este ejercicio forma parte del curso

Introducción a las canalizaciones de datos

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Instrucciones de ejercicio

  • Use the appropriate ETL function to extract data from the raw_data.csv file.
  • Load the raw_data DataFrame into the raw_data table in a data warehouse.
  • Call the transform() function to transform the data in the raw_data source table.

Ejercicio interactivo práctico

Pruebe este ejercicio completando este código de muestra.

# Extract data from the raw_data.csv file
raw_data = ____(file_name="____.csv")

# Load the extracted_data to the raw_data table
load(data_frame=____, table_name="____")

# Transform data in the raw_data table
____(
  source_table="____", 
  target_table="cleaned_data"
)
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