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DP-700 · Question #82

You have two Fabric notebooks named Load_Salesperson and Load_Orders that read data from Parquet files in a lakehouse. Load_Salesperson writes to a Delta table named dim_salesperson. Load_Orders…

DAG = { "activities": [ { "name": "Load_Salesperson", "path": "Load_Salesperson", "timeoutPerCellInSeconds": 300 }, { "name": "Load_Orders", "path": "Load_Orders", "timeoutPerCellInSeconds": 600, "dependencies": ["Load_Salesperson"] } ], "timeoutInSeconds": 43200 }…

Design and implement data ingestion and transformation

Question

You have two Fabric notebooks named Load_Salesperson and Load_Orders that read data from Parquet files in a lakehouse. Load_Salesperson writes to a Delta table named dim_salesperson. Load_Orders writes to a Delta table named fact_orders and is dependent on the successful execution of Load_Salesperson. You need to implement a pattern to dynamically execute Load_Salesperson and Load_Orders in the appropriate order by using a notebook. How should you complete the code? To answer, drag the appropriate values the correct targets. Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.

Exhibit

DP-700 question #82 exhibit

Explanation

DAG = { "activities": [ { "name": "Load_Salesperson", "path": "Load_Salesperson", "timeoutPerCellInSeconds": 300 }, { "name": "Load_Orders", "path": "Load_Orders", "timeoutPerCellInSeconds": 600, "dependencies": ["Load_Salesperson"] } ], "timeoutInSeconds": 43200 } mssparkutils.notebook.runMultiple(DAG)

Topics

#Fabric notebooks#Notebook orchestration#Data pipelines#Delta Lake

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