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!
Deze oefening maakt deel uit van de cursus
ETL and ELT in Python
Oefeninstructies
- Update the
transform()function to call the.execute()method on thedata_warehouseobject. - Use the newly-updated
transform()function to populate data in thetotal_salestarget table by transforming data in theraw_sales_datasource table.
Praktische interactieve oefening
Probeer deze oefening eens door deze voorbeeldcode in te vullen.
# 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="____")