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You have a Fabric tenant that contains a new semantic model in OneLake. You use a Fabric notebook to read the data into a Spark DataFrame. You need to evaluate the data to calculate the min, max, mean, and standard deviation values for all the string and numeric columns. Solution: You use the following PySpark expression: df.show() Does this meet the goal?
You have a Fabric tenant that contains a lakehouse named lakehouse1. Lakehouse1 contains a table named Table1. You are creating a new data pipeline. You plan to copy external data to Table1. The schema of the external data changes regularly. You need the copy operation to meet the following requirements: Replace Table1 with the schema of the external data. Replace all the data in Table1 with the rows in the external data. You add a Copy data activity to the pipeline. What should you do for the Copy data activity?
You need to create a data loading pattern for a Type 1 slowly changing dimension (SCD). Which two actions should you include in the process? Each correct answer presents part of the solution. NOTE: Each correct answer is worth one point.
You have a Fabric tenant that contains a warehouse. You use a dataflow to load a new dataset from OneLake to the warehouse. You need to add a Power Query step to identify the maximum values for the numeric columns. Which function should you include in the step?
You have a Fabric workspace named Workspace 1 that contains a dataflow named Dataflow1. Dataflow! has a query that returns 2.000 rows. You view the query in Power Query as shown in the following exhibit.

What can you identify about the pickupLongitude column?
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