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| Section | Weight | Objectives |
|---|---|---|
| Ingest and transform data | 30-35% | - Transform data using Dataflows Gen2 and notebooks - Ingest data using Data Factory pipelines and Dataflows Gen2 - Design and implement loading patterns - Optimize and manage Delta tables - Ingest and transform data using eventstreams |
| Implement and manage an analytics solution | 30-35% | - Implement lifecycle management and source control for analytics assets - Configure and manage workspace settings and item access - Orchestrate processes with Data Factory pipelines - Implement security and governance |
| Monitor and optimize an analytics solution | 30-35% | - Optimize performance of data storage and queries - Monitor Fabric items - Implement error handling in pipelines |
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NEW QUESTION # 14
Your company has a team of developers. The team creates Python libraries of reusable code that is used to transform data.
You create a Fabric workspace name Workspace1 that will be used to develop extract, transform, and load (ETL) solutions by using notebooks.
You need to ensure that the libraries are available by default to new notebooks in Workspace1.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
Answer:
Explanation:
Explanation:
NEW QUESTION # 15
HOTSPOT
You are building a data loading pattern for Fabric notebook workloads.
You have the following code segment:
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
NEW QUESTION # 16
DRAG DROP
You have a Fabric eventhouse that contains a KQL database. The database contains a table named TaxiData.
The following is a sample of the data in TaxiData.
You need to build two KQL queries. The solution must meet the following requirements:
One of the queries must partition RunningTotalAmount by VendorID.
The other query must create a column named FirstPickupDateTime that shows the first value of each hour from tpep_pickup_datetime partitioned by payment_type.
How should you complete each query? 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.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Partition the RunningTotalAmount by VendorID. - Row_cumsum
The Row_cumsum function computes the cumulative sum of a column while optionally restarting the accumulation based on a condition. In this case, it calculates the cumulative sum of total_amount for each VendorID, restarting when the VendorID changes (VendorID != prev(VendorID)).
Create a column FirstPickupDateTime that shows the first value of each hour from tpep_pickup_datetime, partitioned by payment_type - Row_window_session
NEW QUESTION # 17
You have a Fabric lakehouse that contains the resources shown in the following table.
You need to use a notebook to query for customers in the United States and load the filtered data into USCustomers. The solution must minimize the number of scripts used.
Which statement should you use?
Answer: C
NEW QUESTION # 18
You have a Fabric workspace named Workspace1 that contains three notebooks named notebook_01, notebook_02, and notebook_03.
You are building a new notebook in Workspace1 that will contain the following Directed Acyclic Graph (DAG) definition.
You need to modify the DAG definition to meet the following requirements:
* Ensure that notebook.01 and notebook_02 run in parallel.
* Ensure that notebook_02 only runs after the execution of notebook_03 is complete.
How should you modify the DAG definition?
Answer: C
NEW QUESTION # 19
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