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
Instrucciones de ejercicio
- Use the appropriate ETL function to extract data from the
raw_data.csv
file. - Load the
raw_data
DataFrame into theraw_data
table in a data warehouse. - Call the
transform()
function to transform the data in theraw_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"
)