The "T" in ELT
Let's not forget about ELT! Here, the extract()
and load()
functions have been defined for you. Now, all that's left is to finish defining the transform()
function and run the pipeline. Go get 'em!
Este ejercicio forma parte del curso
Introducción a las canalizaciones de datos
Instrucciones de ejercicio
- Update the
transform()
function to call the.execute()
method on thedata_warehouse
object. - Use the newly-updated
transform()
function to populate data in thetotal_sales
target table by transforming data in theraw_sales_data
source table.
Ejercicio interactivo práctico
Pruebe este ejercicio completando este código de muestra.
# Complete building the transform() function
def transform(source_table, target_table):
data_warehouse.____(f"""
CREATE TABLE {target_table} AS
SELECT
CONCAT("Product ID: ", product_id),
quantity * price
FROM {source_table};
""")
extracted_data = extract(file_name="raw_sales_data.csv")
load(data_frame=extracted_data, table_name="raw_sales_data")
# Populate total_sales by transforming raw_sales_data
____(source_table="____", target_table="____")